From f3771aba7e097f769bd5b538a8347c9d40c1b7e5 Mon Sep 17 00:00:00 2001
From: Antony Lee <anntzer.lee@gmail.com>
Date: Sun, 30 Nov 2014 14:19:51 -0800
Subject: [PATCH 01/14] Saner defaults for peak_local_max, untested.

First attempt at fixing #1246.
---
 skimage/feature/peak.py | 21 +++++++++++++--------
 1 file changed, 13 insertions(+), 8 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 421abeec..26177837 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -3,9 +3,9 @@ import scipy.ndimage as ndi
 from ..filters import rank_order
 
 
-def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
-                   exclude_border=True, indices=True, num_peaks=np.inf,
-                   footprint=None, labels=None):
+def peak_local_max(image, min_distance=10, threshold_abs=-np.inf,
+                   threshold_rel=None, exclude_border=True, indices=True,
+                   num_peaks=np.inf, footprint=None, labels=None):
     """
     Find peaks in an image, and return them as coordinates or a boolean array.
 
@@ -28,7 +28,8 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
     threshold_abs : float
         Minimum intensity of peaks.
     threshold_rel : float
-        Minimum intensity of peaks calculated as `max(image) * threshold_rel`.
+        Minimum intensity of peaks calculated as `max(image) * threshold_rel`;
+        not used if set to None (the default).
     exclude_border : bool
         If True, `min_distance` excludes peaks from the border of the image as
         well as from each other.
@@ -42,7 +43,7 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
     footprint : ndarray of bools, optional
         If provided, `footprint == 1` represents the local region within which
         to search for peaks at every point in `image`.  Overrides
-        `min_distance`, except for border exclusion if `exclude_border=True`.
+        `min_distance` (also for `exclude_border`).
     labels : ndarray of ints, optional
         If provided, each unique region `labels == value` represents a unique
         region to search for peaks. Zero is reserved for background.
@@ -138,12 +139,16 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
         # zero out the image borders
         for i in range(image.ndim):
             image = image.swapaxes(0, i)
-            image[:min_distance] = 0
-            image[-min_distance:] = 0
+            remove = (footprint.shape[i] if footprint is not None
+                      else 2 * min_distance)
+            image[:remove // 2] = 0
+            image[-remove // 2:] = 0
             image = image.swapaxes(0, i)
 
     # find top peak candidates above a threshold
-    peak_threshold = max(np.max(image.ravel()) * threshold_rel, threshold_abs)
+    peak_threshold = threshold_abs
+    if threshold_rel is not None:
+        peak_threshold = max(peak_threshold, image.max())
 
     # get coordinates of peaks
     coordinates = np.argwhere(image > peak_threshold)

From 58283e7bd5fbb1e32a03834721d98257cdd4cb7a Mon Sep 17 00:00:00 2001
From: Antony Lee <anntzer.lee@gmail.com>
Date: Sun, 30 Nov 2014 23:09:53 -0800
Subject: [PATCH 02/14] Change default min_distance; improve docstring.

---
 skimage/feature/peak.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 26177837..fd2c7047 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -3,7 +3,7 @@ import scipy.ndimage as ndi
 from ..filters import rank_order
 
 
-def peak_local_max(image, min_distance=10, threshold_abs=-np.inf,
+def peak_local_max(image, min_distance=1, threshold_abs=-np.inf,
                    threshold_rel=None, exclude_border=True, indices=True,
                    num_peaks=np.inf, footprint=None, labels=None):
     """
@@ -19,25 +19,25 @@ def peak_local_max(image, min_distance=10, threshold_abs=-np.inf,
     ----------
     image : ndarray of floats
         Input image.
-    min_distance : int
+    min_distance : int, optional
         Minimum number of pixels separating peaks in a region of `2 *
         min_distance + 1` (i.e. peaks are separated by at least
         `min_distance`). If `exclude_border` is True, this value also excludes
         a border `min_distance` from the image boundary.
         To find the maximum number of peaks, use `min_distance=1`.
-    threshold_abs : float
+    threshold_abs : float, optional
         Minimum intensity of peaks.
-    threshold_rel : float
+    threshold_rel : float, optional
         Minimum intensity of peaks calculated as `max(image) * threshold_rel`;
         not used if set to None (the default).
-    exclude_border : bool
+    exclude_border : bool, optional
         If True, `min_distance` excludes peaks from the border of the image as
         well as from each other.
-    indices : bool
-        If True, the output will be an array representing peak coordinates.
-        If False, the output will be a boolean array shaped as `image.shape`
-        with peaks present at True elements.
-    num_peaks : int
+    indices : bool, optional
+        If True (the default), the output will be an array representing peak
+        coordinates.  If False, the output will be a boolean array shaped as
+        `image.shape` with peaks present at True elements.
+    num_peaks : int, optional
         Maximum number of peaks. When the number of peaks exceeds `num_peaks`,
         return `num_peaks` peaks based on highest peak intensity.
     footprint : ndarray of bools, optional

From bd2ecff62f444fce081a3b9ceb54469d8024d34b Mon Sep 17 00:00:00 2001
From: Antony Lee <anntzer.lee@gmail.com>
Date: Wed, 21 Jan 2015 17:14:05 -0800
Subject: [PATCH 03/14] WIP: fix impl. of peak_local_max, update tests.

---
 skimage/feature/corner.py            |  2 +-
 skimage/feature/peak.py              | 24 ++++-----
 skimage/feature/tests/test_corner.py | 77 ++++++++++++++++++----------
 skimage/feature/tests/test_peak.py   | 33 +++++++-----
 4 files changed, 84 insertions(+), 52 deletions(-)

diff --git a/skimage/feature/corner.py b/skimage/feature/corner.py
index 6081e1a2..e8d31abe 100644
--- a/skimage/feature/corner.py
+++ b/skimage/feature/corner.py
@@ -799,7 +799,7 @@ def corner_subpix(image, corners, window_size=11, alpha=0.99):
     return corners_subpix
 
 
-def corner_peaks(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
+def corner_peaks(image, min_distance=1, threshold_abs=None, threshold_rel=None,
                  exclude_border=True, indices=True, num_peaks=np.inf,
                  footprint=None, labels=None):
     """Find corners in corner measure response image.
diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index fd2c7047..8bac92bf 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -3,7 +3,7 @@ import scipy.ndimage as ndi
 from ..filters import rank_order
 
 
-def peak_local_max(image, min_distance=1, threshold_abs=-np.inf,
+def peak_local_max(image, min_distance=1, threshold_abs=None,
                    threshold_rel=None, exclude_border=True, indices=True,
                    num_peaks=np.inf, footprint=None, labels=None):
     """
@@ -28,8 +28,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=-np.inf,
     threshold_abs : float, optional
         Minimum intensity of peaks.
     threshold_rel : float, optional
-        Minimum intensity of peaks calculated as `max(image) * threshold_rel`;
-        not used if set to None (the default).
+        Minimum intensity of peaks, calculated as `max(image) * threshold_rel`.
     exclude_border : bool, optional
         If True, `min_distance` excludes peaks from the border of the image as
         well as from each other.
@@ -124,7 +123,6 @@ def peak_local_max(image, min_distance=1, threshold_abs=-np.inf,
         else:
             return out
 
-    image = image.copy()
     # Non maximum filter
     if footprint is not None:
         image_max = ndi.maximum_filter(image, footprint=footprint,
@@ -133,22 +131,24 @@ def peak_local_max(image, min_distance=1, threshold_abs=-np.inf,
         size = 2 * min_distance + 1
         image_max = ndi.maximum_filter(image, size=size, mode='constant')
     mask = (image == image_max)
-    image *= mask
 
     if exclude_border:
         # zero out the image borders
-        for i in range(image.ndim):
-            image = image.swapaxes(0, i)
+        for i in range(mask.ndim):
+            mask = mask.swapaxes(0, i)
             remove = (footprint.shape[i] if footprint is not None
                       else 2 * min_distance)
-            image[:remove // 2] = 0
-            image[-remove // 2:] = 0
-            image = image.swapaxes(0, i)
+            mask[:remove // 2] = mask[-remove // 2:] = False
+            mask = mask.swapaxes(0, i)
 
     # find top peak candidates above a threshold
-    peak_threshold = threshold_abs
+    thresholds = []
+    if threshold_abs is not None:
+        thresholds.append(threshold_abs)
     if threshold_rel is not None:
-        peak_threshold = max(peak_threshold, image.max())
+        thresholds.append(threshold_rel * image.max())
+    if thresholds:
+        mask &= image > max(thresholds)
 
     # get coordinates of peaks
     coordinates = np.argwhere(image > peak_threshold)
diff --git a/skimage/feature/tests/test_corner.py b/skimage/feature/tests/test_corner.py
index 953e47e3..e8db0b46 100644
--- a/skimage/feature/tests/test_corner.py
+++ b/skimage/feature/tests/test_corner.py
@@ -107,21 +107,25 @@ def test_square_image():
     im[:25, :25] = 1.
 
     # Moravec
-    results = peak_local_max(corner_moravec(im))
+    results = peak_local_max(corner_moravec(im),
+                             min_distance=10, threshold_rel=0)
     # interest points along edge
     assert len(results) == 57
 
     # Harris
-    results = peak_local_max(corner_harris(im, method='k'))
+    results = peak_local_max(corner_harris(im, method='k'),
+                             min_distance=10, threshold_rel=0)
     # interest at corner
     assert len(results) == 1
 
-    results = peak_local_max(corner_harris(im, method='eps'))
+    results = peak_local_max(corner_harris(im, method='eps'),
+                             min_distance=10, threshold_rel=0)
     # interest at corner
     assert len(results) == 1
 
     # Shi-Tomasi
-    results = peak_local_max(corner_shi_tomasi(im))
+    results = peak_local_max(corner_shi_tomasi(im),
+                             min_distance=10, threshold_rel=0)
     # interest at corner
     assert len(results) == 1
 
@@ -133,18 +137,22 @@ def test_noisy_square_image():
     im = im + np.random.uniform(size=im.shape) * .2
 
     # Moravec
-    results = peak_local_max(corner_moravec(im))
+    results = peak_local_max(corner_moravec(im),
+                             min_distance=10, threshold_rel=0)
     # undefined number of interest points
     assert results.any()
 
     # Harris
-    results = peak_local_max(corner_harris(im, sigma=1.5, method='k'))
+    results = peak_local_max(corner_harris(im, method='k'),
+                             min_distance=10, threshold_rel=0)
     assert len(results) == 1
-    results = peak_local_max(corner_harris(im, sigma=1.5, method='eps'))
+    results = peak_local_max(corner_harris(im, method='eps'),
+                             min_distance=10, threshold_rel=0)
     assert len(results) == 1
 
     # Shi-Tomasi
-    results = peak_local_max(corner_shi_tomasi(im, sigma=1.5))
+    results = peak_local_max(corner_shi_tomasi(im, sigma=1.5),
+                             min_distance=10, threshold_rel=0)
     assert len(results) == 1
 
 
@@ -156,11 +164,13 @@ def test_squared_dot():
     # Moravec fails
 
     # Harris
-    results = peak_local_max(corner_harris(im))
+    results = peak_local_max(corner_harris(im),
+                             min_distance=10, threshold_rel=0)
     assert (results == np.array([[6, 6]])).all()
 
     # Shi-Tomasi
-    results = peak_local_max(corner_shi_tomasi(im))
+    results = peak_local_max(corner_shi_tomasi(im),
+                             min_distance=10, threshold_rel=0)
     assert (results == np.array([[6, 6]])).all()
 
 
@@ -173,20 +183,26 @@ def test_rotated_img():
     im_rotated = im.T
 
     # Moravec
-    results = peak_local_max(corner_moravec(im))
-    results_rotated = peak_local_max(corner_moravec(im_rotated))
+    results = peak_local_max(corner_moravec(im),
+                             min_distance=10, threshold_rel=0)
+    results_rotated = peak_local_max(corner_moravec(im_rotated),
+                                     min_distance=10, threshold_rel=0)
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
 
     # Harris
-    results = peak_local_max(corner_harris(im))
-    results_rotated = peak_local_max(corner_harris(im_rotated))
+    results = peak_local_max(corner_harris(im),
+                             min_distance=10, threshold_rel=0)
+    results_rotated = peak_local_max(corner_harris(im_rotated),
+                                     min_distance=10, threshold_rel=0)
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
 
     # Shi-Tomasi
-    results = peak_local_max(corner_shi_tomasi(im))
-    results_rotated = peak_local_max(corner_shi_tomasi(im_rotated))
+    results = peak_local_max(corner_shi_tomasi(im),
+                             min_distance=10, threshold_rel=0)
+    results_rotated = peak_local_max(corner_shi_tomasi(im_rotated),
+                                     min_distance=10, threshold_rel=0)
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
 
@@ -195,7 +211,8 @@ def test_subpix_edge():
     img = np.zeros((50, 50))
     img[:25, :25] = 255
     img[25:, 25:] = 255
-    corner = peak_local_max(corner_harris(img), num_peaks=1)
+    corner = peak_local_max(corner_harris(img),
+                            min_distance=10, threshold_rel=0, num_peaks=1)
     subpix = corner_subpix(img, corner)
     assert_array_equal(subpix[0], (24.5, 24.5))
 
@@ -203,7 +220,8 @@ def test_subpix_edge():
 def test_subpix_dot():
     img = np.zeros((50, 50))
     img[25, 25] = 255
-    corner = peak_local_max(corner_harris(img), num_peaks=1)
+    corner = peak_local_max(corner_harris(img),
+                            min_distance=10, threshold_rel=0, num_peaks=1)
     subpix = corner_subpix(img, corner)
     assert_array_equal(subpix[0], (25, 25))
 
@@ -214,7 +232,8 @@ def test_subpix_no_class():
     assert_array_equal(subpix[0], (np.nan, np.nan))
 
     img[25, 25] = 1e-10
-    corner = peak_local_max(corner_harris(img), num_peaks=1)
+    corner = peak_local_max(corner_harris(img),
+                            min_distance=10, threshold_rel=0, num_peaks=1)
     subpix = corner_subpix(img, np.array([[25, 25]]))
     assert_array_equal(subpix[0], (np.nan, np.nan))
 
@@ -223,7 +242,7 @@ def test_subpix_border():
     img = np.zeros((50, 50))
     img[1:25,1:25] = 255
     img[25:-1,25:-1] = 255
-    corner = corner_peaks(corner_harris(img), min_distance=1)
+    corner = corner_peaks(corner_harris(img), threshold_rel=0)
     subpix = corner_subpix(img, corner, window_size=11)
     ref = np.array([[ 0.52040816,  0.52040816],
                     [ 0.52040816, 24.47959184],
@@ -244,7 +263,8 @@ def test_num_peaks():
 
     for i in range(20):
         n = np.random.random_integers(20)
-        results = peak_local_max(img_corners, num_peaks=n)
+        results = peak_local_max(img_corners,
+                                 min_distance=10, threshold_rel=0, num_peaks=n)
         assert (results.shape[0] == n)
 
 
@@ -252,14 +272,16 @@ def test_corner_peaks():
     response = np.zeros((5, 5))
     response[2:4, 2:4] = 1
 
-    corners = corner_peaks(response, exclude_border=False)
+    corners = corner_peaks(response, exclude_border=False, min_distance=10,
+                           threshold_rel=0)
     assert len(corners) == 1
 
-    corners = corner_peaks(response, exclude_border=False, min_distance=0)
+    corners = corner_peaks(response, exclude_border=False, min_distance=0,
+                           threshold_rel=0)
     assert len(corners) == 4
 
     corners = corner_peaks(response, exclude_border=False, min_distance=0,
-                           indices=False)
+                           threshold_rel=0, indices=False)
     assert np.sum(corners) == 4
 
 
@@ -323,7 +345,8 @@ def test_corner_fast_lena():
                         [492, 139],
                         [494, 169],
                         [496, 266]])
-    actual = corner_peaks(corner_fast(img, 12, 0.3))
+    actual = corner_peaks(corner_fast(img, 12, 0.3),
+                          min_distance=10, threshold_rel=0)
     assert_array_equal(actual, expected)
 
 
@@ -355,7 +378,6 @@ def test_corner_orientations_astronaut():
                          -4.40598471e-01,  3.14918803e-01, -1.76069982e+00,
                           3.05330950e+00,  2.39291733e+00, -1.22091334e-01,
                          -3.09279990e-01,  1.45931342e+00])
-
     actual = corner_orientations(img, corners, octagon(3, 2))
     assert_almost_equal(actual, expected)
 
@@ -363,7 +385,8 @@ def test_corner_orientations_astronaut():
 def test_corner_orientations_square():
     square = np.zeros((12, 12))
     square[3:9, 3:9] = 1
-    corners = corner_peaks(corner_fast(square, 9), min_distance=1)
+    corners = corner_peaks(corner_fast(square, 9),
+                           min_distance=1, threshold_rel=0)
     actual_orientations = corner_orientations(square, corners, octagon(3, 2))
     actual_orientations_degrees = np.rad2deg(actual_orientations)
     expected_orientations_degree = np.array([  45.,  135.,  -45., -135.])
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
index e6256208..43a87369 100644
--- a/skimage/feature/tests/test_peak.py
+++ b/skimage/feature/tests/test_peak.py
@@ -70,12 +70,14 @@ def test_num_peaks():
     image[1, 5] = 12
     image[3, 5] = 8
     image[5, 3] = 7
-    assert len(peak.peak_local_max(image, min_distance=1)) == 5
-    peaks_limited = peak.peak_local_max(image, min_distance=1, num_peaks=2)
+    assert len(peak.peak_local_max(image, min_distance=1, threshold_abs=0)) == 5
+    peaks_limited = peak.peak_local_max(
+        image, min_distance=1, threshold_abs=0, num_peaks=2)
     assert len(peaks_limited) == 2
     assert (1, 3) in peaks_limited
     assert (1, 5) in peaks_limited
-    peaks_limited = peak.peak_local_max(image, min_distance=1, num_peaks=4)
+    peaks_limited = peak.peak_local_max(
+        image, min_distance=1, threshold_abs=0, num_peaks=4)
     assert len(peaks_limited) == 4
     assert (1, 3) in peaks_limited
     assert (1, 5) in peaks_limited
@@ -272,7 +274,8 @@ def test_disk():
                                  min_distance=1, threshold_rel=0,
                                  indices=False, exclude_border=False)
     assert np.all(result)
-    result = peak.peak_local_max(image, footprint=footprint)
+    result = peak.peak_local_max(image, footprint=footprint, indices=False,
+                                 exclude_border=False)
     assert np.all(result)
 
 
@@ -280,11 +283,14 @@ def test_3D():
     image = np.zeros((30, 30, 30))
     image[15, 15, 15] = 1
     image[5, 5, 5] = 1
-    assert_equal(peak.peak_local_max(image), [[15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, min_distance=6), [[15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, exclude_border=False),
+    assert_equal(peak.peak_local_max(image, min_distance=10, threshold_rel=0),
+                 [[15, 15, 15]])
+    assert_equal(peak.peak_local_max(image, min_distance=6, threshold_rel=0),
+                 [[15, 15, 15]])
+    assert_equal(peak.peak_local_max(image, min_distance=10, threshold_rel=0,
+                                     exclude_border=False),
                  [[5, 5, 5], [15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, min_distance=5),
+    assert_equal(peak.peak_local_max(image, min_distance=5, threshold_rel=0),
                  [[5, 5, 5], [15, 15, 15]])
 
 
@@ -292,11 +298,14 @@ def test_4D():
     image = np.zeros((30, 30, 30, 30))
     image[15, 15, 15, 15] = 1
     image[5, 5, 5, 5] = 1
-    assert_equal(peak.peak_local_max(image), [[15, 15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, min_distance=6), [[15, 15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, exclude_border=False),
+    assert_equal(peak.peak_local_max(image, min_distance=10, threshold_rel=0),
+                 [[15, 15, 15, 15]])
+    assert_equal(peak.peak_local_max(image, min_distance=6, threshold_rel=0),
+                 [[15, 15, 15, 15]])
+    assert_equal(peak.peak_local_max(image, min_distance=10, threshold_rel=0,
+                                     exclude_border=False),
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
-    assert_equal(peak.peak_local_max(image, min_distance=5),
+    assert_equal(peak.peak_local_max(image, min_distance=5, threshold_rel=0),
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
 
 

From fe9d7c73a1f8a9a46e83b9e6fabdb812d6ab6388 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 10:27:44 +0100
Subject: [PATCH 04/14] Fix coordinate extraction

---
 skimage/feature/peak.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 8bac92bf..dd4c824c 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -151,10 +151,11 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
         mask &= image > max(thresholds)
 
     # get coordinates of peaks
-    coordinates = np.argwhere(image > peak_threshold)
+    coordinates = np.transpose(mask.nonzero())
 
     if coordinates.shape[0] > num_peaks:
-        intensities = image.flat[np.ravel_multi_index(coordinates.transpose(),image.shape)]
+        intensities = image.flat[np.ravel_multi_index(coordinates.transpose(),
+                                                      image.shape)]
         idx_maxsort = np.argsort(intensities)[::-1]
         coordinates = coordinates[idx_maxsort][:num_peaks]
 

From 5751b0cb28f1300468b06344e5a3cf231b3d0f29 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 10:37:29 +0100
Subject: [PATCH 05/14] Some improvements to the doc string and code formatting

---
 skimage/feature/peak.py | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index dd4c824c..4366923f 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -6,15 +6,17 @@ from ..filters import rank_order
 def peak_local_max(image, min_distance=1, threshold_abs=None,
                    threshold_rel=None, exclude_border=True, indices=True,
                    num_peaks=np.inf, footprint=None, labels=None):
-    """
-    Find peaks in an image, and return them as coordinates or a boolean array.
+    """Find peaks in an image as coordinate list or boolean mask.
 
     Peaks are the local maxima in a region of `2 * min_distance + 1`
     (i.e. peaks are separated by at least `min_distance`).
 
-    NOTE: If peaks are flat (i.e. multiple adjacent pixels have identical
+    If peaks are flat (i.e. multiple adjacent pixels have identical
     intensities), the coordinates of all such pixels are returned.
 
+    If both `threshold_abs` and `threshold_rel` are provided, the maximum
+    of the two is chosen as the minimum intensity threshold of peaks.
+
     Parameters
     ----------
     image : ndarray of floats
@@ -33,7 +35,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
         If True, `min_distance` excludes peaks from the border of the image as
         well as from each other.
     indices : bool, optional
-        If True (the default), the output will be an array representing peak
+        If True, the output will be an array representing peak
         coordinates.  If False, the output will be a boolean array shaped as
         `image.shape` with peaks present at True elements.
     num_peaks : int, optional
@@ -58,10 +60,10 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
     Notes
     -----
     The peak local maximum function returns the coordinates of local peaks
-    (maxima) in a image. A maximum filter is used for finding local maxima.
-    This operation dilates the original image. After comparison between
-    dilated and original image, peak_local_max function returns the
-    coordinates of peaks where dilated image = original.
+    (maxima) in an image. A maximum filter is used for finding local maxima.
+    This operation dilates the original image. After comparison of the dilated
+    and original image, this function returns the coordinates or a mask of the
+    peaks where the dilated image equals the original image.
 
     Examples
     --------
@@ -90,7 +92,9 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
     array([[10, 10, 10]])
 
     """
+
     out = np.zeros_like(image, dtype=np.bool)
+
     # In the case of labels, recursively build and return an output
     # operating on each label separately
     if labels is not None:
@@ -130,7 +134,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
     else:
         size = 2 * min_distance + 1
         image_max = ndi.maximum_filter(image, size=size, mode='constant')
-    mask = (image == image_max)
+    mask = image == image_max
 
     if exclude_border:
         # zero out the image borders

From 3f912903cb5cfa7f031ed044723cc9ae8bef4a7d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 10:45:13 +0100
Subject: [PATCH 06/14] Fix corner orientations unit test

---
 skimage/feature/tests/test_corner.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/skimage/feature/tests/test_corner.py b/skimage/feature/tests/test_corner.py
index e8db0b46..27f67b10 100644
--- a/skimage/feature/tests/test_corner.py
+++ b/skimage/feature/tests/test_corner.py
@@ -365,7 +365,8 @@ def test_corner_orientations_even_shape_error():
 @test_parallel()
 def test_corner_orientations_astronaut():
     img = rgb2gray(data.astronaut())
-    corners = corner_peaks(corner_fast(img, 11, 0.35))
+    corners = corner_peaks(corner_fast(img, 11, 0.35),
+                           min_distance=10, threshold_abs=0, threshold_rel=0.1)
     expected = np.array([-1.75220190e+00,  2.01197383e+00, -2.01162417e+00,
                          -1.88247204e-01,  1.19134149e+00, -6.61151410e-01,
                          -2.99143370e+00,  2.17103132e+00, -7.52950306e-04,

From 88ee3ce96e5d7db62d700c1d81615fa15a0ba282 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 10:55:14 +0100
Subject: [PATCH 07/14] Raise error for invalid min_distance values

---
 skimage/feature/peak.py            | 5 ++++-
 skimage/feature/tests/test_peak.py | 9 ++++++++-
 2 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 4366923f..8aaf9119 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -19,7 +19,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
 
     Parameters
     ----------
-    image : ndarray of floats
+    image : ndarray
         Input image.
     min_distance : int, optional
         Minimum number of pixels separating peaks in a region of `2 *
@@ -93,6 +93,9 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
 
     """
 
+    if min_distance < 1:
+        raise ValueError("`min_disance` must greater than 0")
+
     out = np.zeros_like(image, dtype=np.bool)
 
     # In the case of labels, recursively build and return an output
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
index 43a87369..e6a08eef 100644
--- a/skimage/feature/tests/test_peak.py
+++ b/skimage/feature/tests/test_peak.py
@@ -1,6 +1,6 @@
 import numpy as np
 from numpy.testing import (assert_array_almost_equal as assert_close,
-                           assert_equal)
+                           assert_equal, assert_raises)
 from scipy import ndimage as ndi
 from skimage.feature import peak
 
@@ -309,6 +309,13 @@ def test_4D():
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
 
 
+def test_invalid_min_distance():
+    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
+                  min_distance=0)
+    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
+                  min_distance=-1)
+
+
 if __name__ == '__main__':
     from numpy import testing
     testing.run_module_suite()

From 024c4328f20a5d4e98779259f9bc67126311e95d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 10:56:13 +0100
Subject: [PATCH 08/14] Fix corner_peaks doctest

---
 skimage/feature/corner.py | 9 ++-------
 1 file changed, 2 insertions(+), 7 deletions(-)

diff --git a/skimage/feature/corner.py b/skimage/feature/corner.py
index e8d31abe..08d4cfd7 100644
--- a/skimage/feature/corner.py
+++ b/skimage/feature/corner.py
@@ -823,18 +823,13 @@ def corner_peaks(image, min_distance=1, threshold_abs=None, threshold_rel=None,
            [ 0.,  0.,  1.,  1.,  0.],
            [ 0.,  0.,  1.,  1.,  0.],
            [ 0.,  0.,  0.,  0.,  0.]])
-    >>> peak_local_max(response, exclude_border=False)
+    >>> peak_local_max(response)
     array([[2, 2],
            [2, 3],
            [3, 2],
            [3, 3]])
-    >>> corner_peaks(response, exclude_border=False)
+    >>> corner_peaks(response)
     array([[2, 2]])
-    >>> corner_peaks(response, exclude_border=False, min_distance=0)
-    array([[2, 2],
-           [2, 3],
-           [3, 2],
-           [3, 3]])
 
     """
 

From e74da89ede6f1e4d6100bc9885b312d00dd5ccad Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 11:01:41 +0100
Subject: [PATCH 09/14] Fix corner_fast doctest

---
 skimage/feature/corner.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/skimage/feature/corner.py b/skimage/feature/corner.py
index 08d4cfd7..fef9b046 100644
--- a/skimage/feature/corner.py
+++ b/skimage/feature/corner.py
@@ -610,7 +610,7 @@ def corner_fast(image, n=12, threshold=0.15):
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
-    >>> corner_peaks(corner_fast(square, 9), min_distance=1)
+    >>> corner_peaks(corner_fast(square, 9), min_distance=1, threshold_rel=0.1)
     array([[3, 3],
            [3, 8],
            [8, 3],

From bbb427b9eab3e966c70c7142c1048c9fa9df6eb6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 11:03:04 +0100
Subject: [PATCH 10/14] Fix peak_local_max doctest

---
 skimage/feature/peak.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 8aaf9119..76f27a76 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -3,7 +3,7 @@ import scipy.ndimage as ndi
 from ..filters import rank_order
 
 
-def peak_local_max(image, min_distance=1, threshold_abs=None,
+def peak_local_max(image, min_distance=1, threshold_abs=0,
                    threshold_rel=None, exclude_border=True, indices=True,
                    num_peaks=np.inf, footprint=None, labels=None):
     """Find peaks in an image as coordinate list or boolean mask.

From dfae40f9a815cfc3b842de3f7c5206d96f6b17c6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 18:29:27 +0100
Subject: [PATCH 11/14] Change default threshold_abs value to minimum image
 intensity

---
 skimage/feature/peak.py              | 13 ++++++-------
 skimage/feature/tests/test_corner.py | 11 +++++------
 skimage/feature/tests/test_peak.py   | 14 ++++----------
 3 files changed, 15 insertions(+), 23 deletions(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 76f27a76..d3e3f4f5 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -3,7 +3,7 @@ import scipy.ndimage as ndi
 from ..filters import rank_order
 
 
-def peak_local_max(image, min_distance=1, threshold_abs=0,
+def peak_local_max(image, min_distance=1, threshold_abs=None,
                    threshold_rel=None, exclude_border=True, indices=True,
                    num_peaks=np.inf, footprint=None, labels=None):
     """Find peaks in an image as coordinate list or boolean mask.
@@ -28,7 +28,8 @@ def peak_local_max(image, min_distance=1, threshold_abs=0,
         a border `min_distance` from the image boundary.
         To find the maximum number of peaks, use `min_distance=1`.
     threshold_abs : float, optional
-        Minimum intensity of peaks.
+        Minimum intensity of peaks. By default, the absolute threshold is
+        the minimum intensity of the image.
     threshold_rel : float, optional
         Minimum intensity of peaks, calculated as `max(image) * threshold_rel`.
     exclude_border : bool, optional
@@ -93,9 +94,6 @@ def peak_local_max(image, min_distance=1, threshold_abs=0,
 
     """
 
-    if min_distance < 1:
-        raise ValueError("`min_disance` must greater than 0")
-
     out = np.zeros_like(image, dtype=np.bool)
 
     # In the case of labels, recursively build and return an output
@@ -150,8 +148,9 @@ def peak_local_max(image, min_distance=1, threshold_abs=0,
 
     # find top peak candidates above a threshold
     thresholds = []
-    if threshold_abs is not None:
-        thresholds.append(threshold_abs)
+    if threshold_abs is None:
+        threshold_abs = image.min()
+    thresholds.append(threshold_abs)
     if threshold_rel is not None:
         thresholds.append(threshold_rel * image.max())
     if thresholds:
diff --git a/skimage/feature/tests/test_corner.py b/skimage/feature/tests/test_corner.py
index 27f67b10..c3919fe8 100644
--- a/skimage/feature/tests/test_corner.py
+++ b/skimage/feature/tests/test_corner.py
@@ -269,19 +269,18 @@ def test_num_peaks():
 
 
 def test_corner_peaks():
-    response = np.zeros((5, 5))
-    response[2:4, 2:4] = 1
+    response = np.zeros((10, 10))
+    response[2:5, 2:5] = 1
 
     corners = corner_peaks(response, exclude_border=False, min_distance=10,
                            threshold_rel=0)
     assert len(corners) == 1
 
-    corners = corner_peaks(response, exclude_border=False, min_distance=0,
-                           threshold_rel=0)
+    corners = corner_peaks(response, exclude_border=False, min_distance=1)
     assert len(corners) == 4
 
-    corners = corner_peaks(response, exclude_border=False, min_distance=0,
-                           threshold_rel=0, indices=False)
+    corners = corner_peaks(response, exclude_border=False, min_distance=1,
+                           indices=False)
     assert np.sum(corners) == 4
 
 
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
index e6a08eef..8161ca39 100644
--- a/skimage/feature/tests/test_peak.py
+++ b/skimage/feature/tests/test_peak.py
@@ -272,11 +272,12 @@ def test_disk():
     result = peak.peak_local_max(image, labels=np.ones((10, 20)),
                                  footprint=footprint,
                                  min_distance=1, threshold_rel=0,
-                                 indices=False, exclude_border=False)
-    assert np.all(result)
-    result = peak.peak_local_max(image, footprint=footprint, indices=False,
+                                 threshold_abs=-1, indices=False,
                                  exclude_border=False)
     assert np.all(result)
+    result = peak.peak_local_max(image, footprint=footprint, threshold_abs=-1,
+                                 indices=False, exclude_border=False)
+    assert np.all(result)
 
 
 def test_3D():
@@ -309,13 +310,6 @@ def test_4D():
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
 
 
-def test_invalid_min_distance():
-    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
-                  min_distance=0)
-    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
-                  min_distance=-1)
-
-
 if __name__ == '__main__':
     from numpy import testing
     testing.run_module_suite()

From e552002e72285aa1ec44668ddb3647ad5bd9b97c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 18:31:22 +0100
Subject: [PATCH 12/14] Fix BRIEF test cases

---
 skimage/feature/tests/test_brief.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/skimage/feature/tests/test_brief.py b/skimage/feature/tests/test_brief.py
index 610dc984..7f6ae9b7 100644
--- a/skimage/feature/tests/test_brief.py
+++ b/skimage/feature/tests/test_brief.py
@@ -18,7 +18,8 @@ def test_normal_mode():
     """Verify the computed BRIEF descriptors with expected for normal mode."""
     img = data.coins()
 
-    keypoints = corner_peaks(corner_harris(img), min_distance=5)
+    keypoints = corner_peaks(corner_harris(img), min_distance=5,
+                             threshold_abs=0, threshold_rel=0.1)
 
     extractor = BRIEF(descriptor_size=8, sigma=2)
 
@@ -40,7 +41,8 @@ def test_uniform_mode():
     """Verify the computed BRIEF descriptors with expected for uniform mode."""
     img = data.coins()
 
-    keypoints = corner_peaks(corner_harris(img), min_distance=5)
+    keypoints = corner_peaks(corner_harris(img), min_distance=5,
+                             threshold_abs=0, threshold_rel=0.1)
 
     extractor = BRIEF(descriptor_size=8, sigma=2, mode='uniform')
 

From 91ed3780194b200b9008f158d1f1c8aaceab7fef Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Sun, 24 Jan 2016 18:41:11 +0100
Subject: [PATCH 13/14] Fix bug in exclude_border option

---
 skimage/feature/peak.py            |  2 +-
 skimage/feature/tests/test_peak.py | 13 +++++++++++++
 2 files changed, 14 insertions(+), 1 deletion(-)

diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index d3e3f4f5..0cc1b26d 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -137,7 +137,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
         image_max = ndi.maximum_filter(image, size=size, mode='constant')
     mask = image == image_max
 
-    if exclude_border:
+    if exclude_border and (footprint is not None or min_distance > 0):
         # zero out the image borders
         for i in range(mask.ndim):
             mask = mask.swapaxes(0, i)
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
index 8161ca39..40292cd9 100644
--- a/skimage/feature/tests/test_peak.py
+++ b/skimage/feature/tests/test_peak.py
@@ -310,6 +310,19 @@ def test_4D():
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
 
 
+def test_threshold_rel_default():
+    image = np.ones((5, 5))
+
+    image[2, 2] = 1
+    assert len(peak.peak_local_max(image)) == 0
+
+    image[2, 2] = 2
+    assert_equal(peak.peak_local_max(image), [[2, 2]])
+
+    image[2, 2] = 0
+    assert len(peak.peak_local_max(image, min_distance=0)) == image.size - 1
+
+
 if __name__ == '__main__':
     from numpy import testing
     testing.run_module_suite()

From 433523805ff04df6603d560e69d0d4ba9ab60847 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= <jsch@demuc.de>
Date: Fri, 29 Jan 2016 09:23:36 +0100
Subject: [PATCH 14/14] Fix matching test cases

---
 skimage/feature/tests/test_match.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/skimage/feature/tests/test_match.py b/skimage/feature/tests/test_match.py
index 31d20d36..770dc37b 100644
--- a/skimage/feature/tests/test_match.py
+++ b/skimage/feature/tests/test_match.py
@@ -36,11 +36,13 @@ def test_binary_descriptors_lena_rotation_crosscheck_false():
 
     extractor = BRIEF(descriptor_size=512)
 
-    keypoints1 = corner_peaks(corner_harris(img), min_distance=5)
+    keypoints1 = corner_peaks(corner_harris(img), min_distance=5,
+                              threshold_abs=0, threshold_rel=0.1)
     extractor.extract(img, keypoints1)
     descriptors1 = extractor.descriptors
 
-    keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
+    keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5,
+                              threshold_abs=0, threshold_rel=0.1)
     extractor.extract(rotated_img, keypoints2)
     descriptors2 = extractor.descriptors
 
@@ -69,11 +71,13 @@ def test_binary_descriptors_lena_rotation_crosscheck_true():
 
     extractor = BRIEF(descriptor_size=512)
 
-    keypoints1 = corner_peaks(corner_harris(img), min_distance=5)
+    keypoints1 = corner_peaks(corner_harris(img), min_distance=5,
+                              threshold_abs=0, threshold_rel=0.1)
     extractor.extract(img, keypoints1)
     descriptors1 = extractor.descriptors
 
-    keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
+    keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5,
+                              threshold_abs=0, threshold_rel=0.1)
     extractor.extract(rotated_img, keypoints2)
     descriptors2 = extractor.descriptors