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