Nguyễn Công Phương

DIGITAL IMAGE PROCESSING

Introduction

Contents

Introduction to Image Processing & Matlab Image Acquisition, Types, & File I/O Image Arithmetic

Image Transform Spatial & Frequency Domain Filter Design Image Restoration & Blind Deconvolution

Binary Image Processing Image Encryption & Watermarking Image Classification & Segmentation

I. II. III. IV. Affine & Logical Operations, Distortions, & Noise in Images V. VI. VII. VIII. Image Compression IX. Edge Detection X. XI. XII. XIII. Image – Based Object Tracking XIV. Face Recognition XV. Soft Computing in Image Processing

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References

[1] A. Das. Guide to Signals and Patterns in Image Processing: Foundation, Methods and Application. Springer, 2015. [2] W. K. Pratt. Introduction to Digital Image Processing. CRC Press, 2014. [3] U. Qidwai, C. H. Chen. Digital Image Processing: An Algorithmic Approach with MATLAB®. CRC Press, 2009. [4] L. P. Yaroslavsky. Theoretical Foundations of Digital Imaging using MATLAB®. CRC Press, 2013. [5] sites.google.com/site/ncpdhbkhn

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Introduction

1. What is an Image? 2. Image Properties 3. Why Matlab?

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What is an Image? (1)

y

• A digital image is a 2D

signal.

• An image is a function (e.g., brightness) of two real variable a(x,y): – a: amplitude, real number

or integer,

– (x,y): real coordinate

position.

x

0

• Pixel: picture element. • Region of interest (ROI).

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What is an Image? (2)

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Image Properties (1)

• Signal – to – Noise Ratio (SNR):

SNR

power signal _ noise power _

• Image bit resolution (or image resolution): the number of grayscale level or the number of pixels present in the image.

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Image Properties (2)

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Image Properties (3)

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Why Matlab?

• Images can be treated as matrices. • Matlab is optimized for matrix operations. • So …

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