DS4151 Digital Image and Video Processing Syllabus:
DS4151 Digital Image and Video Processing Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To provide the student with basic understanding of image fundamentals and transforms
To provide exposure to the students about image enhancement and restoration
To impart a thorough understanding about segmentation and Recognition.
To know the Video Processing and motion estimation
Learning the concepts will enable students to design and develop an image processing application .
UNIT I FUNDAMENTALS OF IMAGE PROCESSING AND TRANSFORMS
Introduction, Image sampling, Quantization, Resolution, Image file formats, Elements of image processing system, Need for transform, image transforms, Fourier transform, 2 D Discrete Fourier transform ,Walsh transform, Hadamard transform, Haar transform, KL transform, singular value decomposition, Radon transform, comparison of different image transforms. Digital Camera working principle.
UNIT II ENHANCEMENT AND RESTORATION
Spatial domain methods: Histogram processing, Fundamentals of Spatial filtering, Smoothing spatial filters, Sharpening spatial filters. Frequency domain methods: Basics of filtering in frequency domain, image smoothing, image sharpening, Introduction to Image restoration, Image degradation, Image restoration model, Linear and Nonlinear image restoration techniques, Blind deconvolution. Color image enhancement.
UNIT III SEGMENTATION AND RECOGNITION
Edge detection, Edge linking via Hough transform – Thresholding – Region based segmentation – Region growing – Region splitting and merging – Morphological processing- erosion and dilation, Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture – Patterns and Pattern classes – Recognition based on matching.
UNIT IV BASIC STEPS OF VIDEO PROCESSING
Analog Video, Digital Video. Time-Varying Image Formation models: Three- Dimensional Motion Models, Geometric Image Formation, Photometric Image Formation, Sampling of Video signals, Filtering operations
UNIT V 2-D MOTION ESTIMATION
Optical flow, optical flow constraints, General Methodologies, Pixel Based Motion Estimation, Block Matching Algorithm, Mesh based Motion Estimation, Global Motion Estimation, Region based Motion Estimation, Multi resolution motion estimation, Waveform based coding, Block based transform coding, Predictive coding, Application of motion estimation in Video coding.
45 PERIODS
PRACTICAL EXERCISES: 30 PERIODS
1. Histogram Equalization
2. Image Filtering (spatial-domain)
3. Image Filtering (frequency-domain)
4. Image Segmentation
5. Familiarization with Video Processing tools
6. Denoising video
7. Video resizing
8. Background subtraction
9. Interpolation methods for re-sampling
10. Adaptive unsharp masking based interpolation for video up-sampling
11. Gaussian mixture model (GMM) based background subtraction
12. Video encoding
COURSE OUTCOMES:
On the successful completion of the course, students will be able to
CO1: Analyze the digital image, representation of digital image and digital images in transform Domain.
CO2: Analyze the detection of point, line and edges in images and understand the redundancy in images, various image compression techniques.
CO3: Analyze the video technology from analog color TV systems to digital video systems, how video signal is sampled and filtering operations in video processing.
CO4: Obtain knowledge in general methodologies for 2D motion estimation, various coding used in video processing.
CO5: Design image and video processing systems.
TOTAL:75 PERIODS
REFERENCES:
1. Digital Image Processing – Gonzalez and Woods, 3rd Ed., Pearson, 2016
2. Handbook of Image and Video processing, Academic press, 2010
3. K.R.Castelman, Digital Image processing, Prentice Hall, 1996
4. Anil Kumar Jain, Fundamentals of Digital Image Processing, Prentice Hall of India.2nd edition, 2002
5. R C Gonzalez, R E Woods and S L Eddins, Digital Image Processing Using Matlab, Pearson Education , 2006