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# histeq() - Image Processing

### Syntax

### Example

### Output / Return Value

### Limitations

### Alternatives / See Also

### Reference

J = histeq(I,hgram) transforms the intensity image I so that the histogram of the output intensity image J with length(hgram) bins approximately matches hgram. The vector hgram should contain integer counts for equally spaced bins with intensity values in the appropriate range: [0, 1] for images of class double, [0, 255] for images of class uint8, and [0, 65535] for images of class uint16. histeq automatically scales hgram so that sum(hgram) = prod(size(I)). The histogram of J will better match hgram when length(hgram) is much smaller than the number of discrete levels in I.J = histeq(I,n) transforms the intensity image I, returning in J an intensity image with n discrete gray levels. A roughly equal number of pixels is mapped to each of the n levels in J, so that the histogram of J is approximately flat. (The histogram of J is flatter when n is much smaller than the number of discrete levels in I.) The default value for n is 64.[J, T] = histeq(I) returns the grayscale transformation that maps gray levels in the image I to gray levels in J.[gpuarrayJ, gpuarrayT] = histeq(gpuarrayI,___) performs the histogram equalization on a GPU. The input image and the output image are gpuArrays. This syntax requires the Parallel Computing Toolboxâ„˘.newmap = histeq(X, map, hgram) transforms the colormap associated with the indexed image X so that the histogram of the gray component of the indexed image (X,newmap) approximately matches hgram. The histeq function returns the transformed colormap in newmap. length(hgram) must be the same as size(map,1).newmap = histeq(X, map) transforms the values in the colormap so that the histogram of the gray component of the indexed image X is approximately flat. It returns the transformed colormap in newmap.[newmap, T] = histeq(X,___) returns the grayscale transformation T that maps the gray component of map to the gray component of newmap.Code Generation support: Yes.MATLAB Function Block support: Yes.

J = histeq(I,hgram)J = histeq(I,n)[J, T] = histeq(I)[gpuarrayJ, gpuarrayT] = histeq(gpuarrayI,___)newmap = histeq(X, map, hgram)newmap = histeq(X, map)[newmap, T] = histeq(X,___)

I = imread('tire.tif'); J = histeq(I); imshow(I) figure, imshow(J)