EC-801B: Digital Image Processing

Instructor: Dr. Tribeni Prasad Banerjee [Room No-GF-036]

Course Name: Digital Image Processing

Code: 801B

Date and Schedule Time: As per routine [Even Semester_2016]

Course Objective:

Digital image processing deals with processing of images which are digital in nature. Study of the subject is motivated by three major applications. The first application is in improvement of pictorial information for human perception i.e. enhancing the quality of the image so that the image will have a better look. The second is for autonomous machine applications which have wider applications in industries, particularly for quality control in assembly automation and many similar applications. This course will introduce various image processing techniques, algorithms and their applications.

Course Outcomes:

After the successfully completing course, the student -can understand about Image sampling and quantization color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration.

Emphasis is on the general principles of image processing.

Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices.

Course Syllabus/Content:

Introduction, Image Representation, Color Space, Image Sampling, Quantization, Image Quality Measurement, Image Quality Enhancement, Discrete Fourier Transform, Frequency-Domain Filtering, Image Transform, Discrete Cosine Transform, KL Transform, Image Restoration, Image Feature Extraction and Representation: Edge and Line, Region Segmentation and Representation,Morphological Image Processing, Image and Video Compression,Object Recognition.

Course/Lecture Plan:

Module:1

Week 1:

Lec_1 to Lec_3:Introduction and signal digitization

Week 2:

Lec_4 to Lec_6:Pixel relationship

Week 3:

Lec_7 to Lec_9:Camera models & imaging geometry

Module:2

Week 4:

Lec_10 to Lec_13:Image interpolation, Fourier Transform and Frequency Domain Filtering.

Week 5:

Lec_14 to Lec_17:Image transformation, DCT, KL Transform

Week 6:

Lec_18 to Lec_20:Image enhancement I

Week 7:

Lec_21 to Lec_23:Image enhancement II

Week 8:

Lec_24 to Lec_26:Image enhancement III

Module 3:

Week 9:

Lec_27 to Lec_30:Image restoration I

Week 10:

Lec_31 to Lec_33:Image restoration II & Image registration

Week 11:

Lec_34 to Lec_36:Colour and Video image processing

Module 4:

Week 12:

Lec_37 to Lec_39:Image segmentation

Week 13:

Lec_40 to Lec_42:Morphological image processing, Image Compression

Week 14:

Lec_43 to Lec_45:Object representation, description and recognition

Course Assessments:

1] Homework Assignments [20%]

2] Termpaper / Projects [40%]

3] Midterm/Classtest [40%]

References Books:

1. Digital Image Processing by Rafael C Gonzalez & Richard E Woods, 3rd Edition

2. Fundamentals of Digital Image Processing by Anil K Jain

3. Digital Image Processing by William K Pratt

Web resource: