S. Mandayam/ DIP/ECE Dept./Rowan University Introduction to Digital Image Processing Shreekanth Mandayam ECE Department Rowan University shreek/spring03/cc

S. Mandayam/ DIP/ECE Dept./Rowan University

Introduction to Introduction to Digital Image Digital Image ProcessingProcessing

Shreekanth MandayamECE Department

Rowan University

http://engineering.rowan.edu/~shreek/spring03/cc/

February 25, 2003February 25, 2003



Hurricane Fran, TIME Magazine, Sept. 16, 1996Picture Taken by: GOES-8,NASA GODDARD SPACE FLIGHT CENTER







ABA E-13B FontABA E-13B Font





BiometricsBiometrics


Module OverviewModule Overview

• Lecture 1• Digital Image Fundamentals• Digital Image Enhancement

• Lecture 2• Digital Image Segmentation• Digital Image Compression


Lecture 1Lecture 1

Digital Image Fundamentals


Lecture 1: PlanLecture 1: Plan

• What is an image?• Mathematical representation of

monochromatic images• What is a digital image?

• Digital image processing• Fundamental steps• Why do we need this?

• Sampling & Quantization

• Image Preprocessing


ImagesImages

xy

f(x, y)row

column

Sample

Quantize


Monochromatic Digital ImageMonochromatic Digital Image

.....

.....

....120

....256

..1127128 x

y

GrayLevel

f(x,y)


Color ImagesColor Images

R B

G

W

M

CY

Mixtures of Light: Additive Primaries


R+G+BRG

B

R+G+BRG

B

R+G+BRG

B

R+G+BRG

B

R+G+BRG

B

R+G+BRG

B


RGB Color SpaceRGB Color Space


Fundamental Steps*Fundamental Steps*

*Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley, 1992

ImageAcquisition

ImageAcquisition

Preprocessing(Enhancement & Restoration)

Preprocessing(Enhancement & Restoration)

SegmentationSegmentation Representation &Description

Representation &Description

Recognition &Interpretation

Recognition &Interpretation

ProblemDomain

KnowledgeBase

KnowledgeBase

Result


DIP: DetailsDIP: Details

Gray-level Histogram

Spatial

DFT DC T

Spectral

Digital Image Characteristics

Point Processing M asking Filtering

Enhancem ent

Degradation M odels Inverse Filtering W iener Filtering

Restoration

Pre-Processing

Inform ation Theory

LZW (gif)

Lossless

Transform -based (jpeg)

Lossy

Com pression

Edge Detection

Segm entation

Shape Descriptors Texture M orphology

Description

Digital Im age Processing


Sampling & QuantizationSampling & Quantization

• Samplingdemos/demo1sampling_and_quantization/demo_sampling.m

• Quantizationdemos/demo1sampling_and_quantization/demo_quant.m

Digital Image ProcessingCourse Nos. 0909-452-01 (Senior Elective) and 0909-552-01 (Graduate)

Fall 2003

Previous Offering: http://engineering.rowan.edu/~shreek/fall01/dip/


DIP: TopicsDIP: Topics

Gray-level Histogram

Spatial

DFT DC T

Spectral

Digital Image Characteristics

Point Processing M asking Filtering

Enhancem ent

Degradation M odels Inverse Filtering W iener Filtering

Restoration

Pre-Processing

Inform ation Theory

LZW (gif)

Lossless

Transform -based (jpeg)

Lossy

Com pression

Edge Detection

Segm entation

Shape Descriptors Texture M orphology

Description

Digital Im age Processing


Image PreprocessingImage Preprocessing

Enhancement Restoration

SpatialDomain

SpectralDomain

Point Processing• >>imadjust• >>histeq

Spatial filtering• >>filter2

Filtering• >>fft2/ifft2• >>fftshift

• Inverse filtering• Wiener filtering


Point ProcessingPoint Processing(Intensity Transformation)(Intensity Transformation)

s(x,y) = T{ r(x,y)}

TransformedGray Level

OriginalGray Level

TransformationFunction

>>imadjdemo>>imadjust


Point ProcessingPoint Processing

• Pixel Operations

• Point processing

• Histogram equalization

• Connectivity

individual pixels

all pixels

neighboring pixels


Point ProcessingPoint Processing

0 L-1

L-1

0

0 L-1

L-1

0r

s

r

s

r1 r2

s1

s2

>>imadjdemo>>imadjust


Image HistogramImage Histogram

LevelsGray of No.:L

imagein pixels of no. Total :n

k LevelGray with pixels of No. :nn

n)(rp

k

kkr

>>imadjdemo>>imhist


Histogram EqualizationHistogram Equalization(Balancing)(Balancing)

LevelsGray of No.:L

imagein pixels of no. Total :n

k LevelGray with pixels of No. :nn

n)(rp

1,....,2 ,1 ,0 );()(

k

kkr

0

k

jjrkk LkrprTs

>>imadjdemo>>histeq


SummarySummaryDigital Image ProcessingCourse Nos. 0909-452-01 (Senior Elective) and 0909-552-01 (Graduate) Fall 2003

Previous Offering: http://engineering.rowan.edu/~shreek/fall01/dip/

Next Tuesday: Lecture 2

•Digital Image Segmentation

•Digital Image Compression

Documents

S. Mandayam/ DIP/ECE Dept./Rowan University Introduction to Digital Image Processing Shreekanth Mandayam ECE Department Rowan University shreek/spring03/cc