Course Details

1. Be able to identify the components of an image processing system.
2. Be able to work on digital images having binary, grayscale and RGB format.
3. Employ techniques for image enhancement, restoration, coding and compression.
4. Understand image frequencies and transformations
5. Write programs in Matlab or a high level language to implement image processing algorithms.

Introduction to Digital Image Processing: Define and understand the several types of images. Understand concepts of Imaging geometry, Imaging Devices, Image acquisition and Image Representation

Binary Image Processing: Understand binary Image and their creation. Logical Operations on images. Apply algorithms for Blob Coloring, Binary Morphology, Binary Image Compression.

Image Histogram and Point Operations: Understand what the histogram of an Image represents. How can we apply Linear Point operations, Nonlinear point operations, Histogram Shaping and Matching, Algebraic Image Operations, Geometric Image Operations.

Non Linear Gray Scale Image Filtering: Understand concepts of Non-Linear Gray Scale Image filtering and apply filters like median. Understand image noise and modelling.

Discrete Fourier Transform:0 Sinusoidal Image, Discrete Fourier Transform, Meaning of Image Frequencies, Sampling Theorem

Laboratory Work: Read gray scale images, present histogram, find the optimum threshold to transform into binary, Transform gray scale to binary, count blobs, present blobs of images, Binary functions on images, OR, NOT, AND, XOR. Apply morphological filters on images, Use morphological filters on binary images, so as to change the shape. Find the average optical density of a gray level image, apply histogram shifting and scaling. Gray level images, contrast stretch and flattening. Gray level images, histogram fitting, image filtering. Fourier transform, application on images and results verification.

• The Handbook of Image and Video Processing, Al Bovik, Academic Press, 2000.
• Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, 2nd Edition, Addison Wesley Pub. Co, 2002.

• Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing using matlab, 2nd Edition, Addison Wesley Pub. Co, 2002.
• http://www.imageprocessingplace.com/

The taught part of course is delivered to the students by means of lectures, conducted with the help of computer presentations. Lecture notes and presentations are available through the web for students to use in combination with the textbooks.

Practical sessions are held in computer laboratories where Matlab environment is being used and programming exercises are given to gain practical skills and to implement the theoretical concepts taught.