imquantize
Quantize image using specified quantization levels and output values
Syntax
Description
quant_A = imquantize(A,levels)A using specified quantization values contained
in the N-element vector levels. The
quantized image quant_A is the same size as
A and contains N+1 discrete integer
values in the range 1 to N+1. The integer values are determined
by the following criteria:
If
A(k)≤levels(1), thenquant_A(k)=1.If
levels(m–1)<A(k)≤levels(m), thenquant_A(k)=m.If
A(k)>levels(N), thenquant_A(k)=N+1.
Examples
Read an image, convert it to grayscale, and display the result.
I = imread("foggysf2.jpg"); I = rgb2gray(I); imshow(I) title("Grayscale Image")
Calculate two threshold levels.
thresh = multithresh(I,2);
Segment the image into three levels using the imquantize function.
labels = imquantize(I,thresh);
Convert the segmented image into a color image using the label2rgb function, and display the image.
labelsRGB = label2rgb(labels);
imshow(labelsRGB)
title("Segmented Image")
Read and display an RGB image.
I = imread("peppers.png"); imshow(I) title("RGB Image");
Generate thresholds for seven levels from the entire RGB image.
threshRGB = multithresh(I,7);
Generate thresholds for each plane of the RGB image.
threshForPlanes = zeros(3,7); for i = 1:3 threshForPlanes(i,:) = multithresh(I(:,:,i),7); end
Process the entire image with the set of threshold values computed from entire image.
value = [0 threshRGB(2:end) 255]; quantRGB = imquantize(I, threshRGB, value);
Process each RGB plane separately using the threshold vector computed from the given plane. Quantize each RGB plane using threshold vector generated for that plane.
quantPlane = zeros(size(I)); for i = 1:3 value = [0 threshForPlanes(i,2:end) 255]; quantPlane(:,:,i) = imquantize(I(:,:,i),threshForPlanes(i,:),value); end quantPlane = uint8(quantPlane);
Display both posterized images and note the visual differences in the two thresholding schemes.
montage({quantRGB,quantPlane})
title("Full RGB Image Quantization vs. Plane-by-Plane Quantization")
To compare the results, calculate the number of unique RGB pixel vectors in each output image. Note that the plane-by-plane thresholding scheme yields about 23% more colors than the full RGB image scheme.
dim = size(quantRGB); quantRGBmx3 = reshape(quantRGB,prod(dim(1:2)),3); quantPlanemx3 = reshape(quantPlane,prod(dim(1:2)),3); colorsRGB = unique(quantRGBmx3,"rows"); disp("Unique colors in RGB image: "+length(colorsRGB));
Unique colors in RGB image: 188
colorsPlane = unique(quantPlanemx3,"rows"); disp("Unique colors in plane-by-plane image: "+length(colorsPlane));
Unique colors in plane-by-plane image: 231
Reduce the number of discrete levels in an image from 256 to 8. This example uses two different methods for assigning values to each of the eight output levels.
Read image and display it.
I = imread('coins.png'); imshow(I) axis off title('Grayscale Image')
Split the image into eight levels by obtaining seven thresholds from the multithresh function.
thresh = multithresh(I,7);
Construct the valuesMax vector such that the maximum value in each quantization interval is assigned to the eight levels of the output image.
valuesMax = [thresh max(I(:))]
valuesMax = 1×8 uint8 row vector
65 88 119 149 169 189 215 255
[quant8_I_max, index] = imquantize(I,thresh,valuesMax);
Similarly, construct the valuesMin vector such that the minimum value in each quantization interval is assigned to the eight levels of the output image. Instead of calling imquantize again with the vector valuesMin, use the output argument index to assign those values to the output image.
valuesMin = [min(I(:)) thresh]
valuesMin = 1×8 uint8 row vector
23 65 88 119 149 169 189 215
quant8_I_min = valuesMin(index);
Display both eight-level output images side by side.
imshowpair(quant8_I_min,quant8_I_max,'montage') title('Minimum Interval Value Maximum Interval Value')
