RGB2ind ...Three quantization techniques i.e. uniform quantization, minimum variance quantization, and colormap approximations. how we Can apply these quantization approaches to Intensity image or grayscale image alone.

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Please anyone provide the Tutorial or mathematical concept or background how they quantize the images usig three quantization techniques i.e. uniform quantization, minimum variance quantization, and colormap approximations. how we Can apply these quantization approaches to Intensity image or grayscale image alone.
RGB2IND Convert RGB image to indexed image. RGB2IND converts RGB images to indexed images using one of three different methods: uniform quantization, minimum variance quantization, and colormap approximation. RGB2IND dithers the image unless you specify 'nodither' for DITHER_OPTION.
[X,MAP] = RGB2IND(RGB,N) converts the RGB image to an indexed image X
using minimum variance quantization. MAP contains at most N colors. N
must be <= 65536.
X = RGB2IND(RGB,MAP) converts the RGB image to an indexed image X with
colormap MAP by matching colors in RGB with the nearest color in the
colormap MAP. SIZE(MAP,1) must be <= 65536.
[X,MAP] = RGB2IND(RGB,TOL) converts the RGB image to an indexed image X
using uniform quantization. MAP contains at most (FLOOR(1/TOL)+1)^3
colors. TOL must be between 0.0 and 1.0.
[...] = RGB2IND(...,DITHER_OPTION) enables or disables
dithering. DITHER_OPTION is a string that can have one of these values:
'dither' dithers, if necessary, to achieve better color
resolution at the expense of spatial
resolution (default)
'nodither' maps each color in the original image to the
closest color in the new map. No dithering is
performed.
Class Support
-------------
The input image can be of class uint8, uint16, or double. The output
image is of class uint8 if the length of MAP is less than or equal to
256, or uint16 otherwise.
Example
-------
RGB = imread('flowers.tif');
[X,map] = rgb2ind(RGB,128);
imshow(X,map)

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