Unit I

Two-Dimensional Signals and Systems: Sampling in two dimensions: Sampling theorem, Change in Sample rate, Down sampling, Ideal decimation, Up sampling, Ideal interpolation. Continuous Image characterization: Psychophysical vision properties, Photometry, Colorimetry.

Unit II

Fundamentals of Digital Image Processing: Image acquisition – Various modalities, Image sampling and quantization, mathematical representation, Image reconstruction based on interpolation. Gray level transformation, Histogram processing, Arithmetic and logic operations.

Unit III

Transform and filtering: Intensity transformation and spatial filtering, filtering in frequency domain, Image restoration and reconstruction, Binary image morphology. Smoothing and sharpening filters, Line detection, Edge detection, Zero crossings of the second derivative. DFT, smoothing in frequency domain filtering, Sharpening in frequency domain filtering. Degradation model, noise models, restoration in spatial domain,
restoration in frequency domain. Estimation of degradation function, inverse filtering, Wiener filtering, constrained least square filtering.

Unit IV

Color Image Processing: Color Models, the RGB Color Model, the CMY and CMYK Color Models, the HSI Color Model, Pseudo color image processing, Basics of Full Color Image Processing, Smoothing and Sharpening, Image Segmentation Based on Color. Image Segmentation-Point, Line, and Edge Detection, Thresholding-Types Boundary based and Region-Based Segmentation. Representation of Boundary Descriptors, Regional Descriptors-Texture descriptors

Course Description

This course is a broad introduction to vision systems and digital Image Processing . This course includes topics like operation on images, transformation and filtering and Colour Image processing.

Course Objectives

• To understand different operations on images
• To understand image transformation and filtering
• To study colour image processing
• To study image segmentation

Course Outcomes

• CO1: Understand 2D signals and systems
• CO2: Apply sampling in two dimensions
• CO3: Apply fundamentals of digital image processing
• CO4: Analyze transforms and filtering
• CO5: Analyze color image processing

CO-PO Mapping

1. John W Woods, “Multidimensional Signal, Image and Video Processing and Coding”, Academic Press, 2006.
2. Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing”, Third Edition, Pearson Education, 2009.
3. William K. Pratt, “Digital Image Processing”, John Wiley, New York, 2007.
4. Kenneth R. Castleman, “Digital Image Processing”, Prentice Hall, 1996.
5. Gonzalez, Woods and Eddins, “Digital Image Processing using MATLAB”, Prentice Hall, 2004.