JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives

Upon completion of the course, the student will be able to

• 1. Comprehend the image processing fundamentals and enhancement techniques in spatial and frequency domain.
• 2. Describe the color image fundamentals, models and various restoration techniques.
• 3. Design and Analyze the image compression systems.
• 4. Outline the various image segmentation and morphology operations.
• 5. Comprehend the basics of video processing and video coding.

Course Outcomes

After completion of this course, students will be able to –

• 1. Understand theory and models in Image and Video Processing.
• 2. Explain the need of spatial and frequency domain techniques for image compression.
• 3. Comprehend different methods, models for video processing and motion estimation.
• 4. Illustrate quantitative models of image and video segmentation.
• 5. Apply the process of image enhancement for optimal use of resources.

UNIT - I

Digital image fundamentals: A simple image formation model, Image sampling and quantization, Some basic relationships between pixels, Basic intensity transformation functions, Sampling and fourier transform of sampled functions, The discrete fourier transform of one variable, Extensions to functions of two variables (2-D discrete fourier transform, Properties of 2-D DFT and IDFT, 2-D Discrete Convolution Theorem

UNIT - II

Image Enhancement (spatial domain): Histogram processing, Fundamentals of spatial filtering, Smoothing spatial filters, Sharpening spatial filters, The Laplacian-use of second order derivative for image sharpening, The Gradient-use of first order derivative for image sharpening. Image Enhancement (frequency domain): Basics of filtering in frequency domain, Image smoothing using lowpass frequency domain filters, Image sharpening using highpass filters

UNIT - III

Image restoration: Noise Models, Restoration in the presence of noise only – Spatial filters, Periodic noise reduction using Frequency domain filtering, Estimating the degradation function, inverse filtering, Minimum Least square error filtering, constrained least square filters. Wavelet and Multiresolution processing: Matrix-based transform, Walsh-Hadamard Transform, Slant transform, Haar transform.

UNIT - IV

Image compression: Lossy and lossless compression schemes: Huffman coding, Run-length coding, Arithmetic coding, Block transform coding, JPEG Image Morphology: Fundamental operations, Morphological Algorithms. Image segmentation: Point, Line and Edge detection, Canny edge detection, Hough Transform, Edge linking, Thresholding, Region-based segmentation, Pixel-based segmentation.

UNIT - V

Feature Extraction: Boundary preprocessing, Boundary feature descriptor, Region feature descriptor, Principal components as feature descriptor, Whole image feature. Video Processing: Video Formats, Video Enhancement and Restoration, Video Segmentation.

TEXT BOOKS:

• 1. Digital Image Processing, R. C. Gonzalez and R. E. woods, Pearson Education.
• 2. Handbook of Image and Video Processing, AL Bovik, Academic Press.

REFERENCES:

• 1. Digital Image Processing and Analysis, B. Chanda and D. Dutta Mazumdar, PHI.
• 2. Digital Image Processing, W. K. Pratt, Wiley-Interscience.
• 3. Fundamentals of Digital Image Processing, A. K. Jain, Pearson India Education.
• 4. Pattern Classification and Scene Analysis, R. O. Duda and P. E. Hart, Wiley.