Video lecture series in Digital Image Processing, Lecture 9:
Intensity-Gray level (Image negatives, Log and Power-Law) transformations (Point processing functions) for DIP and implementation in MATLAB
#DIP
#DigitalImageProcessing
#DIPusingMATLAB
#StudyWithDrDafda
MATLAB code used in the video is present at the end in the Description
What is Intensity-Gray level transformation function?
What is Image Negative?
What is Log transformation in DIP?
What is Power-Law (Gamma) transformation in DIP?
What is Gamma correction?
What is Point Processing?
Digital Image Processing using MATLAB
Implementation of Intensity(Gray-level) transformations OR Point processing - Image negative, Log transformation and Power-law/Gamma transformation of digital image processing in MATLAB.
Digital Image Processing (DIP) using/in MATLAB
Link to download ppts/lecture notes:
drive.google.c...
Links of other lectures in the series:
1. What is Digital Image Processing?
• What is Digital Image ...
2. Human Visual System and Elements of Digital Image Processing
• Human Visual System an...
3. Fundamental steps in Digital Image Processing
• Fundamental steps in D...
4. Image Sensing and Acquisition
• Image Sensing and Acqu...
5. Relationship between Pixels in Digital Image Processing: Neighborhood, Adjacency & Distance measures
• Relationship between P...
6. Image Sampling and Quantization
• Image Sampling and Qua...
7. Spatial and Intensity resolution in Digital Image Processing and its Implementation in MATLAB
• Spatial and Intensity ...
8. Basics of intensity transformations and spatial filtering and implementation in MATLAB
• Basics of Intensity tr...
% MATLAB program for point transformations
% Image negative, Log transformations, Power-law transformations
close all;
clear all;
clc;
%% Read and display Image
I0=imread('Maulik.png');%Read image information
I=rgb2gray(I0);%Convert Color image to Grayscale image
% I=imread('Cameraman.tif');
montage({I0, I}, 'Size', [1 2]);
title('Color Image Grayscale Image');
%% Image negative
figure
%Id=double(I);
%I_neg = 255-Id;
%montage({I, (uint8(I_neg))}, 'Size', [1 2]);
%title('Original Image Negative Image');
I_neg = imcomplement(I);
montage({I, I_neg}, 'Size', [1 2]);
title('Original Image Negative Image');
%% Log transformation function
figure
Id=im2double(I);
I_log = 0;
[row,col]= size(Id);
C = 3;
for i=1:row
for j=1:col
I_log(i,j) = C*log(1+Id(i,j));
end
end
subplot(1,2,1);
imshow(Id);
title('Original Image');
subplot(1,2,2);
imshow(I_log);
title('Log transformed Image(factor 3)');
%% Log transformation
figure
%I_log = C.*log(1+Id);
Id=im2double(I);
I_log2 = 2 .*log(1+Id);
I_log3 = 3 .*log(1+Id);
I_log4 = 4 .*log(1+Id);
subplot(2,2,1), imshow(Id), title('Original Image');
subplot(2,2,2), imshow(I_log2), title('Log factor 2');
subplot(2,2,3), imshow(I_log3), title('Log factor 3');
subplot(2,2,4), imshow(I_log4), title('Log factor 4');
%% Gamma transformation function
Id=im2double(I);
figure
I_gamma = 0;
[row,col]= size(Id);
C = 0.6;
gamma = 0.3;
for i=1:row
for j=1:col
I_gamma(i,j) = C * Id(i,j)^gamma;
end
end
subplot(1,2,1);
imshow(Id);
title('Original Image');
subplot(1,2,2);
imshow(I_gamma);
title('Gamma transformed Image(factor 3)');
%% Gamma transformation(Gamma greater than 1)
%I_gamma = C * Id.^gamma;
figure
Id=im2double(I);
I_gamma4 = 1 * Id.^3;
I_gamma5= 1 * Id.^4;
I_gamma6 = 1 * Id.^5;
subplot(2,2,1), imshow(Id), title('Original Image');
subplot(2,2,2), imshow(I_gamma4), title('Gamma factor 3');
subplot(2,2,3), imshow(I_gamma5), title('Gamma factor 4');
subplot(2,2,4), imshow(I_gamma6), title('Gamma factor 5');
%% Gamma transformation(Gamma less than 1)
%I_gamma = C * Id.^gamma;
figure
Id=im2double(I);
I_gamma1 = 1 * Id.^0.6;
I_gamma2 = 1 * Id.^0.4;
I_gamma3 = 1 * Id.^0.3;
subplot(2,2,1), imshow(Id), title('Original Image');
subplot(2,2,2), imshow(I_gamma1), title('Gamma factor 0.6');
subplot(2,2,3), imshow(I_gamma2), title('Gamma factor 0.4');
subplot(2,2,4), imshow(I_gamma3), title('Gamma factor 0.3');
1 окт 2024
