'Imshow' diaporamas de présentation

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Chapter 3: Image Display 3.1 Introduction

Chapter 3: Image Display 3.1 Introduction. We look at image quality and how that may be affected by various image attributes For human vision in general, the preference is for images to be sharp and detailed There are many factors that will affect the display ambient lighting,

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A picture is worth more than a 1000 words. It can save a life.

A picture is worth more than a 1000 words. It can save a life. Arjun Watane. Gaussian Derivative. I = imread ( 'brain_tumor_mri_1.jpg' ); I2 = rgb2gray(I); k = fspecial ( ' gaussian ' , [7 7] , 1); %Gaussian filter kernal kdx = conv2(k,[1 0 -1], 'valid' ); %figure; surf( kdx );

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DREAM

DREAM. IDEA. PLAN. IMPLEMENTATION. Introduction to Image Processing. Present to: Amirkabir University of Technology (Tehran Polytechnic) & Semnan University. Dr. Kourosh Kiani Email: kkiani2004@yahoo.com Email: Kourosh.kiani@aut.ac.ir Email : Kourosh.kiani@semnan.ac.ir

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Image Restoration II & Morphological Processing

Image Restoration II & Morphological Processing. Comp344 Tutorial Kai Zhang. Outline. Imgae Degradation Model Inverse Filter Wiener Filter Morphological Processing. Degradation Model. Spatial domain Frequency domain Problem Definition Observe the degraded image g(x,y)

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Edge Magnitude and Orientation

Edge Magnitude and Orientation. Roger S. Gaborski. Matlab Script to Calculate Magnitude and Orientation. First, use slide 90 of lecture 5 as a guide Read in image (in this example, Sign4.jpg from webpage) , convert to double in range [0,1] Convert to grayscale

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Frequency domain Image Processing

Frequency domain Image Processing. Comp344 Tutorial Kai Zhang. Outline. Matlab preliminaries Matlab function design Shifting frequency component Low pass filtering design. Matlab Preliminaries. Basic commands 2d Fourier transform: F = fft2(f, P, Q);

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Frequency domain Image Processing

Frequency domain Image Processing. Comp344 Tutorial Kai Zhang. Outline. Matlab preliminaries Matlab function design Shifting frequency component Low pass filtering design. Matlab Preliminaries. Basic commands 2d Fourier transform: F = fft2(f, P, Q);

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Image enhancement f= imread (E:\PCD2011\PrakPcd\leopard.jpg'); f=ind2gray( f,gray (256));

Image enhancement f= imread (E:PCD2011PrakPcdleopard.jpg'); f=ind2gray( f,gray (256)); imhist (f); f2=max(f1,0.4); % remove all values below 0.4 imshow (f); figure; imshow (f2);.

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