Friday, June 22, 2012
EC2029 DIGITAL IMAGE PROCESSING Syllabus- Anna University
EC2029 DIGITAL IMAGE PROCESSING L T P C
3 0 0 3
AIM
To introduce the student to various image processing techniques.
OBJECTIVES
· To study the image fundamentals and mathematical transforms necessary for image
processing.
· To study the image enhancement techniques
· To study image restoration procedures.
· To study the image compression procedures.
· To study the image segmentation and representation techniques.
UNIT I
DIGITAL IMAGE FUNDAMENTALS
9
Elements of digital image processing systems, Vidicon and Digital Camera working principles, Elements of visual perception, brightness, contrast, hue, saturation, mach band effect, Color image
fundamentals - RGB, HSI models, Image sampling, Quantization, dither, Two-dimensional mathematical preliminaries, 2D transforms - DFT,
DCT, KLT, SVD.
UNIT II IMAGE ENHANCEMENT
9
Histogram equalization and specification techniques, Noise distributions, Spatial
averaging, Directional
Smoothing, Median, Geometric mean, Harmonic mean,
Contraharmonic mean filters, Homomorphic filtering, Color
image enhancement.
UNIT III
IMAGE RESTORATION
9
Image Restoration -
degradation model, Unconstrained restoration -
Lagrange multiplier and Constrained restoration, Inverse filtering-removal of blur caused by uniform linear motion, Wiener filtering, Geometric transformations-spatial
transformations.
UNIT IV IMAGE SEGMENTATION 9
Edge detection, Edge linking via Hough
transform – Thresholding - Region
based segmentation – Region growing
– Region splitting and Merging – Segmentation by
morphological watersheds –
basic concepts –
Dam construction – Watershed
segmentation algorithm.
UNIT V IMAGE COMPRESSION 9
Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, Vector Quantization, Transform
coding, JPEG standard, MPEG.
TOTAL : 45 PERIODS
TEXTBOOK
1. Rafael C. Gonzalez, Richard E. Woods, , Digital Image Processing', Pearson,
Second Edition, 2004.
2. Anil K. Jain, , Fundamentals of Digital
Image Processing', Pearson 2002.
REFERENCES
1. Kenneth R. Castleman, Digital Image Processing, Pearson, 2006.
2. Rafael C. Gonzalez, Richard E. Woods, Steven Eddins,' Digital
Image Processing
using MATLAB', Pearson Education, Inc., 2004.
3. D,E. Dudgeon and RM. Mersereau, , Multidimensional
Digital Signal
Processing', Prentice Hall Professional
Technical Reference, 1990.
4. William K. Pratt, , Digital Image Processing' , John Wiley, New York, 2002
5. Milan Sonka et aI, 'IMAGE PROCESSING, ANALYSIS AND MACHINE VISION',
Brookes/Cole, Vikas Publishing House, 2nd edition, 1999,
By Vinoth
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