subject code:cs1002 department of ece. “one picture is worth more than ten thousand words”...

SUBJECT CODE:CS1002

DEPARTMENT OF ECE

“One picture is worth

more than ten

thousand words”

Anonymous

IMAGE PROCESSING

lens

objec

t

Image FormationImage Formation

image plane

light

sour

ce

Image FormationImage Formation

projection through lens

projection through lens

image of objectimage of object

Image FormationImage Formation

DIGITAL IMAGE PROCESSING

projection onto discrete sensor array.

projection onto discrete sensor array.

Image FormationImage Formation

digital cameradigital camera

sensors register average color.

sensors register average color.

Image FormationImage Formation

sampled imagesampled image

continuous colors, discrete locations.

continuous colors, discrete locations.

Image FormationImage Formation

discrete real-valued image

discrete real-valued image

UNIT-1 DIGITAL IMAGE FUNDAMENTALS AND TRANSFORMS

UNIT-2 IMAGE ENHANCEMENT TECHNIQUES

UNIT-3 IMAGE RESTORATION

UNIT-4 IMAGE COMPRESSION

UNIT-5 IMAGE SEGMENTATION ANDREPRESENTATION

Elements of visual perception – Image sampling and quantization-Basic relationship between pixels-Basic geometric transformationIntroduction to Fourier transform and DFT-Properties of 2D Fourier transform-FFT-Seperable image transformsWalsh hadamard- discrete cosine transform-haar–slanttransform-karhunen–loeve transform

Spatial Domain methods: Basic grey level transformation – Histogram equalization – Image subtraction.Image averaging –Spatial filtering: Smoothing, sharpening filters – Laplacian filters Frequency domain filters : Smoothing – Sharpening filters – Homomorphic filtering

Gray Level Image

HISTOGRAM IMAGE

IMAGE

Model of Image Degradation/restoration process – Noise models – Inverse filtering -Least mean square filtering Constrained least mean square filtering – Blind image restoration – Pseudo inverse – Singular value decomposition.

INVERSE FILTERING

Lossless compression: Variable length coding – LZW coding – Bit plane coding- predictive coding-DPCM

Lossy Compression: Transform coding – Wavelet coding – Basics of Image compression standards: JPEG, MPEG,Basics of Vector quantization

IMAGECOMPRESSION

Edge detection – Thresholding - Region Based segmentation – Boundary representation: chair codes- Polygonal approximation

Boundary segments – boundary descriptors: Simple descriptors-Fourier descriptors - Regional descriptors –Simple descriptors- Texture

EDGE DETECTION

Rafael C Gonzalez, Richard E Woods 2nd Edition, Digital Image Processing - Pearson Education 2003.

1.William K Pratt, Digital Image Processing John Willey (2001)2. Image Processing Analysis and Machine Vision – Millman Sonka, Vaclav hlavac, Roger Boyle, Broos/colic, Thompson Learniy (1999).3. A.K. Jain, PHI, New Delhi (1995)-Fundamentals of Digital Image Processing.4.Chanda Dutta Magundar – Digital Image Processing and Applications, Prentice Hall of India, 2000

www.imageprocessingplace.com

http://www.archive.org/details/Lectures_on_Image_Processing

•Boundary descriptors

•Sharpening filters

•Edge detection

•Image averaging

•Discrete cosine transform•Elements of visual perception.•Thresholding

•Polygonal approximation.•Basics of image compression standards