JNTUH CSE-AIML IMAGE PROCESSING SYLLABUS

Prerequisites
1. Students are expected to have knowledge in linear signals and systems, Fourier Transform,
basic linear algebra, basic probability theory and basic programming techniques; knowledge of
Digital Signal Processing is desirable.
2. A course on “Computational Mathematics”
3. A course on “Computer Oriented Statistical Methods”
Course Objectives
 Provide a theoretical and mathematical foundation of fundamental Digital Image Processing concepts.
 The topics include image acquisition; sampling and quantization; preprocessing; enhancement;restoration; segmentation; and compression.
Course Outcomes
 Demonstrate the knowledge of the basic concepts of two-dimensional signal acquisition,sampling, and quantization.
 Demonstrate the knowledge of filtering techniques.
 Demonstrate the knowledge of 2D transformation techniques.
 Demonstrate the knowledge of image enhancement, segmentation, restoration and compression techniques.
UNIT – I
Digital Image Fundamentals: Digital Image through Scanner, Digital Camera. Concept of Gray Levels.Gray Level to Binary Image Conversion. Sampling and Quantization. Relationship between Pixels.Imaging Geometry. 2D Transformations-DFT, DCT, KLT and SVD.
UNIT – II
Image Enhancement in Spatial Domain Point Processing, Histogram Processing, Spatial Filtering,Enhancement in Frequency Domain, Image Smoothing, Image Sharpening.
UNIT – III
Image Restoration Degradation Model, Algebraic Approach to Restoration, Inverse Filtering, Least Mean Square Filters, Constrained Least Squares Restoration, Interactive Restoration.
UNIT – IV
Image Segmentation Detection of Discontinuities, Edge Linking and Boundary Detection, Thresholding,
Region Oriented Segmentation.
TEXT BOOK:
1. Digital Image Processing: R.C. Gonzalez & R. E. Woods, Addison Wesley/ Pearson Education,2 nd Ed, 2004.
REFERENCE BOOKS:
1. Fundamentals of Digital Image Processing: A. K. Jain, PHI.
2. Digital Image Processing using MAT LAB: Rafael C. Gonzalez, Richard E. Woods, Steven L.Eddins: Pearson Education India, 2004.
3. Digital Image Processing: William K. Pratt, John Wilely, 3rd Edition, 2004
Image Compression Redundancies and their Removal Methods, Fidelity Criteria, Image Compression
Models, Source Encoder and Decoder, Error Free Compression, Lossy Compression.
TEXT BOOK:
1. Digital Image Processing: R.C. Gonzalez & R. E. Woods, Addison Wesley/ Pearson Education,2nd Ed, 2004.
REFERENCE BOOKS:
1. Fundamentals of Digital Image Processing: A. K. Jain, PHI.
2. Digital Image Processing using MAT LAB: Rafael C. Gonzalez, Richard E. Woods, Steven L.
Eddins: Pearson Education India, 2004.
3. Digital Image Processing: William K. Pratt, John Wilely, 3rd Edition, 2004

CSE-AIML