DS7201 ADVANCED DIGITAL IMAGE PROCESSING-ANNA UNIV PG 1ST SEM SYLLABUS - Anna University Internal marks 2018

DS7201 ADVANCED DIGITAL IMAGE PROCESSING-ANNA UNIV PG 1ST SEM SYLLABUS

ANNA UNIVERSITY, CHENNAI
REGULATIONS - 2013
M.E. APPLIED ELECTRONICS
DS7201 ADVANCED DIGITAL IMAGE PROCESSING


COURSE OBJECTIVES:
 To understand the image fundamentals and mathematical transforms necessary for image
processing and to study the image enhancement techniques.
 To understand the image segmentation and representation techniques.
 To understand how image are analyzed to extract features of interest.
 To introduce the concepts of image registration and image fusion.
 To analyze the constraints in image processing when dealing with 3D data sets.

UNIT I FUNDAMENTALS OF DIGITAL IMAGE PROCESSING
Elements of visual perception, brightness, contrast, hue, saturation, mach band effect, 2D
image transforms-DFT, DCT, KLT, and SVD. Image enhancement in spatial and frequency
domain, Review of morphological image processing

UNIT II SEGMENTATION
Edge detection, Thresholding, Region growing, Fuzzy clustering, Watershed algorithm, Active
contour methods, Texture feature based segmentation, Model based segmentation, Atlas based segmentation, Wavelet based Segmentation methods

UNIT III FEATURE EXTRACTION
First and second order edge detection operators, Phase congruency, Localized feature
extraction-detecting image curvature, shape features Hough transform, shape skeletonization,
Boundary descriptors, Moments, Texture descriptors- Autocorrelation, Co-occurrence features,
Runlength features, Fractal model based features, Gabor filter, wavelet features

UNIT IV REGISTRATION AND IMAGE FUSION
Registration- Preprocessing, Feature selection-points, lines, regions and templates Feature
correspondence-Point pattern matching, Line matching, region matching Template matching
.Transformation functions-Similarity transformationand Affine Transformation. Resampling-
Nearest Neighbour and Cubic Splines Image Fusion-Overview of image fusion, pixel fusion,
Multiresolution based fusiondiscrete wavelet transform, Curvelet transform. Region based
fusion.

UNIT V 3D IMAGE VISUALIZATION
Sources of 3D Data sets, Slicing the Data set, Arbitrary section planes, The use of color,
Volumetric display, Stereo Viewing, Ray tracing, Reflection, Surfaces, Multiply connected
surfaces, Image processing in 3D, Measurements on 3D images.

TOTAL: 45 PERIODS

COURSE OUTCOMES:
Upon Completion of the course, the students will be able to
 To understand image formation and the role human visual system plays in perception of
gray and color image data.
 To apply image processing techniques in both the spatial and frequency (Fourier) domains.
 To design image analysis techniques in the form of image segmentation and to evaluate the
methodologies for segmentation.
 To conduct independent study and analysis of feature extraction techniques.
 To understand the concepts of image registration and image fusion.
 To analyze the constraints in image processing when dealing with 3D data sets and to apply
image processing algorithms in practical applications.

TEXT BOOKS:
1. John C.Russ, “The Image Processing Handbook”, CRC Press,2007.
2. Mark Nixon, Alberto Aguado, “Feature Extraction and Image Processing”, Academic Press,
2008.
3. Ardeshir Goshtasby, “ 2D and 3D Image registration for Medical, Remote Sensing and
Industrial Applications”,John Wiley and Sons,2005.
REFERENCE BOOKS:
1. Rafael C. Gonzalez, Richard E. Woods, , Digital Image Processing', Pearson,Education,
Inc., Second Edition, 2004.
2. Anil K. Jain, , Fundamentals of Digital Image Processing', Pearson Education,Inc., 2002.
3. Rick S.Blum,Zheng Liu,“ Multisensor image fusion and its Applications“,Taylor&
Francis,2006.

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