EC2055 DIGITAL IMAGE PROCESSING DIP SYLLABUS | ANNA UNIVERSITY BE E&I 8TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY 8TH SEMESTER B.E ELECTRONICS AND INSTRUMENTATION ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
EC2055 DIGITAL IMAGE PROCESSING L T P C
3 0 0 3
AIM
To introduce the concept of analyzing the digital image fundamentals and digital image
processing.
111
OBJECTIVES:
i. To study the digital image fundamentals and its applications.
ii. To study various filters used in digital image processing.
iii. To study about the segmentation & representation schemes.
iv. To study about recognition & interpretation methods.
v. To study about imagecompression.
UNIT I DIGITAL IMAGE FUNDAMENTALS 9
Elements of visual perception, psycho visual model, brightness, contrast, hue, saturation, mach
band effect, Color image fundamentals -RGB,HSI models, Image sampling, Quantization, dither,
Two-dimensional mathematical formulation.
UNIT II IMAGE TRANSFORMS 9
1D DFT, 2D transforms – DFT, DCT, Discrete Sine, Walsh, Hadamard, Slant, Haar, KLT, SVD,
Wavelet Transform.
UNIT III IMAGE ENHANCEMENT AND RESTORATION 9
Histogram modification and specification techniques, Noise distributions, Spatial averaging,
Directional Smoothing, Median and filters, Homomorphic filtering, Color image enhancement. Image
Restoration – degradation model, Inverse filtering – removal of blur, Wiener filtering, Geometric
transformations – spatial transformations, Gray-Level interpolation,
UNIT IV IMAGE SEGMENTATION AND RECOGNITION 9
Edge detection. Image segmentation by region growing, region splitting and merging, edge linking..
Image Recognition – Patterns and pattern classes, Matching by minimum distance classifier,
Matching by correlation, Image classification using neural network.
UNIT V IMAGE COMPRESSION 9
Need for data compression, Huffman,. Run Length Encoding, Shift codes, Arithmetic coding, Vector
Quantization, Block Truncation Coding. Transform Coding – DCT and Wavelet. JPEG, MPEG.
Standards, principles of Context based Compression . TOTAL : 45 PERIODS TEXT BOOKS:
1. William K.Pratt, ‘ Digital Image Processing’, John Wiley, NewYork,2002.
2. Anil K. Jain, ‘Fundamentals of Digital Image Processing’, Prentice Hall of India, 2002.
REFERENCES:
1. David Salomon : Data Compression – The Complete Reference, Springer Verlag New York Inc.,
2nd Edition, 2001
2. Rafael C. Gonzalez, Richard E.Woods, Steven Eddins, ‘ Digital Image Processing using
MATLAB’, Pearson Education, Inc., 2004.
3. Rafael C. Gonzalez, Richard E.Woods, ‘Digital Image Processing’, Pearson Education, Inc.,
Second Edition, 2004
4. Milman Sonka, Vaclav Hlavac, Roger Boyle, ‘Image Processing, Analysis, and Machine
Vision’, Brooks/Cole, Vikas Publishing House, II ed., 1999.
5. Sid Ahmed, M.A., ‘Image Processing Theory, Algorithms and Architectures’, McGraw-Hill, 1995.
EC2055 DIGITAL IMAGE PROCESSING L T P C
3 0 0 3
AIM
To introduce the concept of analyzing the digital image fundamentals and digital image
processing.
111
OBJECTIVES:
i. To study the digital image fundamentals and its applications.
ii. To study various filters used in digital image processing.
iii. To study about the segmentation & representation schemes.
iv. To study about recognition & interpretation methods.
v. To study about imagecompression.
UNIT I DIGITAL IMAGE FUNDAMENTALS 9
Elements of visual perception, psycho visual model, brightness, contrast, hue, saturation, mach
band effect, Color image fundamentals -RGB,HSI models, Image sampling, Quantization, dither,
Two-dimensional mathematical formulation.
UNIT II IMAGE TRANSFORMS 9
1D DFT, 2D transforms – DFT, DCT, Discrete Sine, Walsh, Hadamard, Slant, Haar, KLT, SVD,
Wavelet Transform.
UNIT III IMAGE ENHANCEMENT AND RESTORATION 9
Histogram modification and specification techniques, Noise distributions, Spatial averaging,
Directional Smoothing, Median and filters, Homomorphic filtering, Color image enhancement. Image
Restoration – degradation model, Inverse filtering – removal of blur, Wiener filtering, Geometric
transformations – spatial transformations, Gray-Level interpolation,
UNIT IV IMAGE SEGMENTATION AND RECOGNITION 9
Edge detection. Image segmentation by region growing, region splitting and merging, edge linking..
Image Recognition – Patterns and pattern classes, Matching by minimum distance classifier,
Matching by correlation, Image classification using neural network.
UNIT V IMAGE COMPRESSION 9
Need for data compression, Huffman,. Run Length Encoding, Shift codes, Arithmetic coding, Vector
Quantization, Block Truncation Coding. Transform Coding – DCT and Wavelet. JPEG, MPEG.
Standards, principles of Context based Compression . TOTAL : 45 PERIODS TEXT BOOKS:
1. William K.Pratt, ‘ Digital Image Processing’, John Wiley, NewYork,2002.
2. Anil K. Jain, ‘Fundamentals of Digital Image Processing’, Prentice Hall of India, 2002.
REFERENCES:
1. David Salomon : Data Compression – The Complete Reference, Springer Verlag New York Inc.,
2nd Edition, 2001
2. Rafael C. Gonzalez, Richard E.Woods, Steven Eddins, ‘ Digital Image Processing using
MATLAB’, Pearson Education, Inc., 2004.
3. Rafael C. Gonzalez, Richard E.Woods, ‘Digital Image Processing’, Pearson Education, Inc.,
Second Edition, 2004
4. Milman Sonka, Vaclav Hlavac, Roger Boyle, ‘Image Processing, Analysis, and Machine
Vision’, Brooks/Cole, Vikas Publishing House, II ed., 1999.
5. Sid Ahmed, M.A., ‘Image Processing Theory, Algorithms and Architectures’, McGraw-Hill, 1995.
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