B.E. Computer Science & Engineering:Digital Image Processing

First Year: Semester I

Mathematics I
Engineering graphics
Computer Programming
Physics
Solid Mechanics
Communication Skill

First Year: Semester-II

Mathematics II
Manufacturing Process
Chemistry
Electrical and Electronic Science
Thermodynamics
Organizational Behavior

Second Year- Semester - I

Measurement Science and Techniques
Optimization Techniques
Semiconductor Devices
Data Structures
Discrete Mathematical Structures
Digital Electronic Circuits
Human Values, Ethics and IPR

Second Year- Semester – II

Numerical and Statistical Methods
Electrical Engineering Materials
Computer System Architecture
Principles of Programming Languages
Analysis and Design of Information Systems
Operating Systems
Environmental Studies


Third Year- Semester – I

Object Oriented Programming
Theory of Computation
Computer Networks
Data Base Management Systems
Software Engineering
Microprocessors
Summer Training

Third Year- Semester – II

Total Quality Management
Algorithm Analysis and Design
Software Project Management
Internet and Web Technologies

Fourth Year- Semester – I

Engineering Economics
System Software
Compiler Construction
Computer Graphics
Artificial Intelligence

Fourth Year- Semester – II

Project Semester
Project
Industrial Training(6 weeks)


Digital Image Processing

Introduction: Digital Image Representation, Fundamental Steps in Image Processing, Elements of Digital Image Processing Systems,

Digital Image Fundamentals: Elements of Visual Perception, A Simple Image Model, Sampling and Quantization, Some Basic Relationships Between Pixels, Imaging Geometry, Photographic Film.

Image Transforms: Introduction to the Fourier Transform, The Discrete Fourier Transform, Some Properties of the two-dimensional Fourier Transform, The Fast Fourier Transform.

Image Enhancement: Background, Enhancement by Point Processing, Spatial filtering, enhancement in the Frequency Domain, Generation of Spatial Masks from Frequency Domain Specifications, Color Image Processing.

Image Restoration: Degradation Model, Diagonalization of Circulant and Block-Circulant Matrices, Algebraic Approach to Restoration, Inverse Filtering.

Image Compression: Fundamentals, Image Compression Models, Elements of Information Theory, Error-Free Compression, Lossy, Compression, Image Compression Standards.