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()