【2】power-law transformation
I=imread('Fig3.08(a).jpg'); subplot(221); imshow(I); title('original');
J=double(I);
I1=im2uint8(mat2gray(J.^0.6)); subplot(222); imshow(I1);
title('power-law:\\gamma=0.6');
I2=im2uint8(mat2gray(J.^0.4)); subplot(223); imshow(I2);
title('power-law:\\gamma=0.4');
I3=im2uint8(mat2gray(J.^0.3)); subplot(224); imshow(I3);
title('power-law:\\gamma=0.3');
Discussion of results
originallog transformation
Figure 3 results of log transformation
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originalpower-law:?=0.6power-law:?=0.4power-law:?=0.3Figure 4 results of power-law transformation
Analysis
Log transformation can diminish dynamic range of the image. Power-law transformation can change the contrast of the image.
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Histogram Equalization
Exp. 6，PROJECT 03-02 [Multiple Uses]
Objective
To manipulate a technique of image enhancement by histogramequalization.
Requirements
(a) Write a computer program for computing the histogram of animage. (b) Implement the histogram equalization technique discussed inSection 3.3.1. (c) Download Fig. 3.8(a) and perform histogram equalization on it.
Figure 5 3.8(a)
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Technical discussion
【1】J = histeq(I, n)
transforms the intensity image I, returning in J an intensity image with n discrete gray levels. 【2】imhist(I)
displays a histogram for the image I above a grayscale colorbar.
Program listings
I=imread('Fig3.08(a).jpg'); subplot(221); imshow(I);
subplot(222); imhist(I);
I1=histeq(I,256); subplot(223) imshow(I1);
subplot(224); imhist(I1);
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Discussion of results
15000100005000001002001500010000500000100200
Figure 6 the results of project 03-02
Analysis
We can see more details in the dark part.
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