- To become familiar with digital image fundamentals
- To get exposed to simple image enhancement techniques in Spatial and Frequency domain.
- To learn concepts of degradation function and restoration techniques.
- To study the image segmentation and representation techniques.
- To become familiar with image compression and recognition methods
UNIT I DIGITAL IMAGE FUNDAMENTALS 9
Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Relationships between pixels -Color image fundamentals – RGB, HSI models, Two-dimensional mathematical preliminaries, 2D transforms – DFT, DCT.
UNIT II IMAGE ENHANCEMENT 9
Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering–Smoothing and Sharpening Spatial Filtering, Frequency Domain: Introduction to Fourier Transform– Smoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian filters, Homomorphic filtering, Color image enhancement
UNIT III IMAGE RESTORATION 9
Image Restoration – degradation model, Properties, Noise models – Mean Filters – Order Statistics – Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering
UNIT IV IMAGE SEGMENTATION 9
Edge detection, Edge linking via Hough transform – Thresholding – Region based segmentation –Region growing – Region splitting and merging – Morphological processing- erosion and dilation,Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed segmentation algorithm.
UNIT V IMAGE COMPRESSION AND RECOGNITION 9
Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, JPEG standard, MPEG. Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture – Patterns and Pattern classes – Recognition based on matching.
TOTAL 45 PERIODS
At the end of the course, the students should be able to:
- Know and understand the basics and fundamentals of digital image processing, such as digitization, sampling, quantization, and 2D-transforms.
- Operate on images using the techniques of smoothing, sharpening and enhancement.
- Understand the restoration concepts and filtering techniques.
- Learn the basics of segmentation, features extraction, compression and recognition methods for color models.
- 1. Rafael C. Gonzalez, Richard E. Woods, ‗Digital Image Processing‘, Pearson, Third Edition,2010.
- 2. Anil K. Jain, ‗Fundamentals of Digital Image Processing‘, Pearson, 2002.
- 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., 2011.
- 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 al ‗Image processing, analysis and machine vision‘, Brookes/Cole, Vikas Publishing House, 2nd edition, 1999
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