Digital Image Processing Lecture 1: Introductioncompe.hku.edu.tr/Dosyalar/COME422--Goruntu-Isleme-ve-Analizi... · Digital Image Processing Lecture 1: Introduction ... 1 General overview

February 24, 2017 1

Digital Image Processing

Lecture 1: Introduction

Lecturer Dr. A.H. Abdul Hafez

Hasan Kalyoncu University

Department of Computer Engineering

HKU, AH Abdul Hafez

February 24, 2017 2

Course Organization and Assessment

1. Course objectives

2. Assessment

3. Lecture plan

4. Text book(s)

5. comments

HKU, AH Abdul Hafez

February 24, 2017 3

Course objectives and learning outcomes

Objectives

1. Study the fundamental concept of the DIP including: Digitization and display

Image enhancement, restoration, encoding, etc.

2. Implementation of some DIP techniques, algorithms, and applications.

Outcomes

1. Understanding the 2D signal processing theory.

2. Familiarization of the basic image processing techniques and its useful applications.

3. Exposure to some advance issues in DIP and computer vision.

HKU, AH Abdul Hafez

February 24, 2017 4

Assessment

1. Two minor exam: 2x15=30%, possibly best 2 out of 3.

2. One major exam: 40%

3. Lab work+assignments: 30%

Important dates:

As faculty schedule

HKU, AH Abdul Hafez

February 24, 2017 5

Lecture’s plan: Theory

Sn Week Sn Week

1 Introduction to DIP systems: What is?,

fields, steps, components.

2 Fundamentals of DIP : forming,

acquisition, representation, resolution, etc.

3 Spatial domain processing: intensity

transformations,

4 Quiz1

Spatial domain processing: histogram, and

thresholding.

5

Spatial domain1 July 2011 processing:

smoothing and sharpening using spatial

filters.

6 Frequency domain processing: 1DFT,

2DFT,

7 Frequency domain processing: smoothing

and sharpening using frequency filtering.

8 Mid-Exam, expected

9 Image restoration , Nonlinear filtering 10 Color image processing

11 Image compression: models, theory.

12 Image compression: techniques and

standards.

13 Image segmentation (regions and edges) 14 Quiz2

15 Review 16 Final Exam Expected HKU, AH Abdul Hafez

February 24, 2017 6

Lecture’s plan: Practice

W Lecture W Lecture

1 General overview of DIP systems 2 Introduction to Matlab

3 Introduction to m-file Matlab programming 4 Intensity transformations and Histogram

5

Spatial filtering: smoothing and sharpening 6

7 Project Discussion and Mini-Practical

Exam

8 Mid-Exam, expected

9 Frequency domain processing 10 Frequency domain processing

11 Project status show case 12 Mathematical Morphology

13 Image compression 14 Edge detection

15 Project discussion and Final Practical

Exam

16 The End

HKU, AH Abdul Hafez

February 24, 2017 7

Text and recommended books

Title Authors Publisher, Date

Comments

Digital Image

Processing

Gonzalez &

Woods

Prentice Hall,

2008, 3rd edition

Theory text book

Digital Image

Processing using

Matlab

Gonzalez, Woods&

Eddins

Prentice Hall, 2004,

2nd edition

Implementation

recommended

Image processing,

analysis, and machine

vision

Milan Sonka, Vaclav

Hlavac, and Roger

Boyle

Thomson Learning,

2008, 3rd edition

Theory recommended

Image processing,

analysis, and machine

vision, A Matlab

companion

Tomáš Svoboda, Jan

Kybic, and Václav

Hlavác.

Thomson Learning,

2007, 1st edition

Implementation

recommended

HKU, AH Abdul Hafez

What is DIP?

An image is defined as 2D function f(x,y)

DIP refers to processing of digital image by means of digital

computers.

Pixel is the basic element of the digital image.

Computer vision Vs image processing: image in image out.

One useful paradigm is

1. Low-level processing: noise reduction, contrast enhancement, and

image sharpening; image in image out.

2. Mid-level processing: segmentation, description, and recognition

(classification); image in attribute out.

3. Higher-level processing: understanding, visual cognition.

February 24, 2017 8 HKU, AH Abdul Hafez

The Origins of DIP

Bartlane cable between London and New York for

newspaper industry in the early 1920s.

1. From more than 1 week to less than 3 hours

2. Specialized printing device for encoding and printing.


The Origins of DIP

The first computer, enough powerful to carry image

processing, appeared in 1960s.

Using computer techniques for improving images from

space probe began in 1964 to remove some distortion

inherited by the on-board camera


The whole range of EM is used for imaging in addition to, ultra-sonic and

electronic .

Imaging in Electro-Magnetic Spectrum



Gamma-Ray Imaging:

A. Complete bone scan.

B. Image of gamma radiation from a valve in a nuclear reactor.



X-ray imaging:

A. Chest X-ray,

B. Head CT.



Imaging in the visible band









Infrared imaging



Imaging in the visual spectrum



Imaging in the visual

spectrum



Imaging in the

Radio Band



Imaging using the ultra sonic waves


February 24, 2017 22

The Human Visual System (HVS)

LGN

primary visual

cortex

higher level vision

and cognition

right eyeleft eye

retina

lens

cornea

fovea

optic nerve

pupil

visual axis

retina retina

HKU, AH Abdul Hafez

HVS: Visual Illusion


Find the black dot

HVS: Visual Illusion


Image Processing: Image Enhancement

Enhance


Image Processing: Image De-noising

Denoise


Image Processing: Image Deblurring

Deblur


Image Analysis: Edge Detection


Image Analysis: Face Detection


Image Analysis: Image Segmentation


Two deceivingly similar fingerprints of two different people

Image Analysis: Image Matching


Image Coding: Image Compression

compressed bitstream 00111000001001101…

(2428 Bytes)

image

encoder

image

decoder

original image 262144 Bytes

compression ratio (CR) = 108:1

From [Gonzalez & Woods]

From [Gonzalez & Woods]


JPEG (CR=64) JPEG2000 (CR=64)

discrete cosine transform based wavelet transform based

Image Coding: From JPEG to JPEG 2000


The End of Lecture 1.


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Digital Image Processing Lecture 1: Introductioncompe.hku.edu.tr/Dosyalar/COME422--Goruntu-Isleme-ve-Analizi... · Digital Image Processing Lecture 1: Introduction ... 1 General overview