Spatial Intensity Resolution Project Using MATLAB with Source Code

Spatial Intensity Resolution of an image Using MATLAB with Source Code

INTRODUCTION

Sampling is the principal factor Estimation of the spatial resolution of an image. Commonly spatial resolution is the smallest perceptible detail in an image, a widely used meaning of resolution is simply the smallest number of discernible line pairs per unit distance; for estimation 100 line pairs/mm.
Gray level resolution: This refers to the smallest visible change in gray level. The measurement of visible changes in gray level is a extremely subjective procedure.

We have significant discretion concerning the number of Samples used to generate a digital image. But this is not true for the amount of gray levels. Due to hardware restraints, the number of gray levels is usually an integer power of two. The most common value is 8 bits. It can vary depending on application. When an actual portion of physical resolution relating pixels and level of detail they resolution in the original scene are not necessary, it is not rare to refer to an L-level digital image of size  as consuming a spatial resolution of  pixels and a gray level resolution of L levels.

Functional Representation of Images
Two-D function f(x,y), (x,y) pixel position. Positive and bounded
Written as f(x,y)=i(x,y)r(x,y), i(x,y) illumination from light source, r(x,y) reflectance (bounded between 0 and 1) based on material properties. E.g r(x,y)=0.01 for black velvet, r(x,y) = 0.93 for snow.
Intensity of monochrome image f(x,y) is synonymous with grey levels. By convention grey level are from 0 to L-1.

Spatial and Gray Level Resolution

Spatial resolution is the lowest level of detail discernable in an image. Number of line sets per millimeter, approximately 100 line pairs per millimeter.
Gray-level resolution is the lowest discernable change in gray level. Very
Subjective.

Image Enhancement in Spatial Domain Find gray level transformation function T(r) to obtains (x,y) =T(f(x,y)) processed image from input image.

REASONS
Contrast enhancement
Image understanding
Visual improvement
Picture Reference:
Photos Reference from Digital Image Processing, Gonzalez and Woods, Copyright 2002

MATLAB Source Code For Spatial Intensity Resolution

clc;
clear all;
close all;
a=imread('C:\Users\natheem\Desktop\images\satelite.jpg');
subplot(3,2,1);
imshow(a);
title('original image');
%
subplot(3,2,2);
imshow(grayslice(a,128),gray(128));
title('128 graylevel image');
%
subplot(3,2,3);
imshow(grayslice(a,64),gray(64));
title('64 graylevel image');
%
subplot(3,2,4);
imshow(grayslice(a,32),gray(32));
title('32 graylevel image');
%
subplot(3,2,5);
imshow(grayslice(a,16),gray(16));
title('16 graylevel image');
%
subplot(3,2,6);
imshow(grayslice(a,8),gray(8));
title('8 graylevel image');

Result

MATLAB PROGRAM USING INDIVIDUAL FIGURE

clc;
clear all;
close all;
a=imread('C:\Users\natheem\Desktop\images\satelite.jpg');
figure(1);
imshow(a);
title('original image');
%128 graylevel image
figure(2);
imshow(grayslice(a,128),gray(128));
title('128 graylevel image');

%64 graylevel image
figure(3);
imshow(grayslice(a,64),gray(64));
title('64 graylevel image');

%32 graylevel image
figure(4);
imshow(grayslice(a,32),gray(32));
title('32 graylevel image');

%16 graylevel imag
figure(5);
imshow(grayslice(a,16),gray(16));
title('16 graylevel image');

%8 graylevel image
figure(6);
imshow(grayslice(a,8),gray(8));
title('8 graylevel image');

Output