kCauchyNearestPatches
Extract the centers of the K best patches with a Cauchy similarity criterion.
Contents
Syntax.
sample = kCauchyNearestPatches( X, gamma ); sample = kCauchyNearestPatches( X, gamma, ...);
Definitions.
Let be ,
and
two patches.
Let define the Cauchy similarity criterion between and
by:
The closest patches are the ones for which is maximum.
Description.
sample = kCauchyNearestPatches( X ); returns, for each pixel of the image, the centers of the K best patches, in the sense of the Cauchy similarity measure, in a search window around the pixel.
Example.
% Load a gray-scale image and set the gamma parameter. input= imread('parrotCauchyNoise_K=5.png'); gamma=5; % Patch extraction. sampleFromPatches = kCauchyNearestPatches(input, gamma,... 'SampleSize', 20,... 'PatchWidth', 3,... 'SearchWindowRadius', 10); % Display the 3rd nearest sample. figure, imshow(uint8(sampleFromPatches(:,:,3))), title('Particular sample.')

Input arguments.
- gamma is the parameter
of the Cauchy similarity measure between patches.
- 'SampleSize' is the number of retained patches. Default value is 30.
- 'PatchWidth' is the width of the patches used for comparison. Default value is 5.
- 'SearchWindowRadius' is the radius of search window. Default value is 10.