Added sections to gallery of examples

Modified travis_script.sh to account for the new structure of the gallery

Added README.txt files in directories of gallery examples

Fixed references to gallery images in user guide pages

Fixed broken links

doc/examples/transform/plot_register_translation.py

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+"""
+=====================================
+Cross-Correlation (Phase Correlation)
+=====================================
+
+In this example, we use phase correlation to identify the relative shift
+between two similar-sized images.
+
+The ``register_translation`` function uses cross-correlation in Fourier space,
+optionally employing an upsampled matrix-multiplication DFT to achieve
+arbitrary subpixel precision. [1]_
+
+.. [1] Manuel Guizar-Sicairos, Samuel T. Thurman, and James R. Fienup,
+       "Efficient subpixel image registration algorithms," Optics Letters 33,
+       156-158 (2008).
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+
+from skimage import data
+from skimage.feature import register_translation
+from skimage.feature.register_translation import _upsampled_dft
+from scipy.ndimage import fourier_shift
+
+image = data.camera()
+shift = (-2.4, 1.32)
+# (-2.4, 1.32) pixel offset relative to reference coin
+offset_image = fourier_shift(np.fft.fftn(image), shift)
+offset_image = np.fft.ifftn(offset_image)
+print("Known offset (y, x):")
+print(shift)
+
+# pixel precision first
+shift, error, diffphase = register_translation(image, offset_image)
+
+fig = plt.figure(figsize=(8, 3))
+ax1 = plt.subplot(1, 3, 1, adjustable='box-forced')
+ax2 = plt.subplot(1, 3, 2, sharex=ax1, sharey=ax1, adjustable='box-forced')
+ax3 = plt.subplot(1, 3, 3)
+
+ax1.imshow(image)
+ax1.set_axis_off()
+ax1.set_title('Reference image')
+
+ax2.imshow(offset_image.real)
+ax2.set_axis_off()
+ax2.set_title('Offset image')
+
+# View the output of a cross-correlation to show what the algorithm is
+#    doing behind the scenes
+image_product = np.fft.fft2(image) * np.fft.fft2(offset_image).conj()
+cc_image = np.fft.fftshift(np.fft.ifft2(image_product))
+ax3.imshow(cc_image.real)
+ax3.set_axis_off()
+ax3.set_title("Cross-correlation")
+
+plt.show()
+
+print("Detected pixel offset (y, x):")
+print(shift)
+
+# subpixel precision
+shift, error, diffphase = register_translation(image, offset_image, 100)
+
+fig = plt.figure(figsize=(8, 3))
+ax1 = plt.subplot(1, 3, 1, adjustable='box-forced')
+ax2 = plt.subplot(1, 3, 2, sharex=ax1, sharey=ax1, adjustable='box-forced')
+ax3 = plt.subplot(1, 3, 3)
+
+ax1.imshow(image)
+ax1.set_axis_off()
+ax1.set_title('Reference image')
+
+ax2.imshow(offset_image.real)
+ax2.set_axis_off()
+ax2.set_title('Offset image')
+
+# Calculate the upsampled DFT, again to show what the algorithm is doing
+#    behind the scenes.  Constants correspond to calculated values in routine.
+#    See source code for details.
+cc_image = _upsampled_dft(image_product, 150, 100, (shift*100)+75).conj()
+ax3.imshow(cc_image.real)
+ax3.set_axis_off()
+ax3.set_title("Supersampled XC sub-area")
+
+
+plt.show()
+
+print("Detected subpixel offset (y, x):")
+print(shift)