Course Title: Digital Image Processing
Semester VI
Course Code BTITC604
Course Type Elective
Pre-requisite
L – T – P - 3 – 0 – 0
Stream Core Credits 3
Course Objectives: 1. To cover the fundamentals and mathematical models in digital image and video processing. 2. To develop time and frequency domain techniques for image enhancement. 3. To expose the students to current technologies and issues in image and video processing. 4. To develop image and video processing applications in practice.
Course Outcomes: At the end of this course, students will be able to: 1. Understand theory and models in Image and Video Processing. 2. Interpret and analyze 2D signals in frequency domain through image transforms. 3. Apply quantitative models of image and video processing for various engineering applications. 4. Develop innovative design for practical applications in various fields.
Course Content:
UNIT I Image fundamentals: Image acquisition, sampling and quantization, image resolution, basic relationship between pixels, color images, RGB, HSI and other models.
UNIT II Two dimensional transforms: 2D-Discrete fourier transform, discrete cosine transform, Walsh Hadamard transform, Haar transform, KL transform, and discrete wavelet transform.
UNIT III Spatial domain Processing: Point processing such as digital negative, contrast stretching, thresholding, gray level slicing, bit plane slicing, log transform and power law transform, neighbourhood processing such as averaging filters, order statistics filters, high pass filters and high boost filters, histogram equalization and histogram specification, frequency domain such as DFT for filtering, ideal, Gaussian and butterwort filters for smoothening and sharpening, and homomorphic filters.
UNIT IV Image segmentation and morphology: Point, line and edge detection, edge linking using Hough transform and graph theoretic approach, thresholding, and region based segmentation, dilation, erosion, opening, closing, hit or miss transform, thinning and thickening, and boundary extraction on binary images.
UNIT V Degradation model, noise models, estimation of degradation function by modelling, restoration using Weiner filters and inverse filters.
UNIT VI Video formation, perception and representation: Digital video sampling, video frame classifications, I, P and B frames, notation, ITU-RBT 601 digital video formats, digital video quality measure, video capture and display: principle of colour video camera, video camera, digital video, sampling of video signals: required sampling rates, sampling in two dimensions and three dimensions, progressive virus interlaced scans, two dimensional motion estimation, block matching algorithms.
Text Books: 1. Gonzales and Woods, "Digital Image Processing", Pearson Education, India, Third Edition. 2. Anil K.Jain, "Fundamentals of Image Processing", Prentice Hall of India, First Edition, 1989.
Reference Books: 1. Ze-Nian Li and Mark S. Drew, "Fundamentals of Multimedia", PHI 2011. 2. Murat Tekalp, "Digital Video Processing", Pearson, 2010. 3. John W. Woods, "Multidimensional Signal, Image and Video Processing", Academic Press 2012. 6. A.I.Bovik, "Handbook on Image and Video Processing", Academic Press.
