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Image/Video Processing and Coding

Module number 1350910

ECTS-Credits

6

Studiengang

Elektrotechnik

Informationstechnik / Technische Informatik

Visual Computing

Computational Engineering

Electrical Engineering

Teacher

Dr.-Ing. Henryk Richter

Semester

Winter semester 3h lectures, 1h seminar

Objectives

Knowledge about basic and advanced image processing algorithms as well as details of classic and modern approaches and standards for image and video coding

Prerequisites

Digitale Signal Processing (recommended)

Content

Introduction

     

  • Perception
  • Imaging Basics
  • Camera Model
  •  

Colors

     

  • CIE XYZ Color Model
  • Color Matching, Color Space Conversion
  • RGB, CMY(K), YCbCr
  •  

Image Processing Basics

     

  • Image Acquisition
  • Image Processing (Improvement, Restoration, Segmentation)
  • Image Analysis (Classification, Interpretation, Recognition)
  •  

Sampling / Quantization

     

  • Image Resampling
  • Anti-Aliasing and Interpolation filtering
  • Linear and Non-Linear Scalar Quantization
  • Vector Quantization
  •  

Discrete Image Characteristics

     

  • Images as 2D Sequences
  • Discrete 2D Systems, Convolution in Time and Frequency Domain
  • Linear and Non-Linear Scalar Quantization
  • Statistical Properties of Images
  •  

Transforms

     

  • General discrete signal transformation, Orthogonality
  • 2D Fourier Transform, 2D DFT
  • DCT, Walsh-Hadamard Transform
  • Wavelets and Filter Banks
  •  

Image Improvement and Restoration

     

  • Pixel based techniques
  • Local spatial filtering techniques
  • Global filtering
  •  

Image Segmentation

     

  • Point-dependent Methods
  • Neighbourhood-dependent Methods
  •  

Feature Extraction

     

  • Features (Shape, Histogram, Spectral, Texture, Color)
  • Feature Selection
  •  

Pattern Recognition

     

  • Classifiers (Distance, Sequential)
  • Neural Networks
  •  

Data Compression Fundamentals

     

  • Source Coding Principles
  • Information, Entropy
  • Coding Characteristics, Quality Evaluation
  •  

Coding

     

  • Entropy Coding (Shannon, Huffmann, Arithmetic)
  • Adaptive Coding
  • Coding for non-iid. sources
  •  

Decorrelation

     

  • Prediction
  • Spectral Decomposition
  •  

Still Image Coding Standards

     

  • JPEG, JPEG-2000
  •  

Video Compression

     

  • Video Compression Basics (Motion Compensation, Picture types and Ordering)
  • Hybrid Video Coding
  • MPEG-1,MPEG-2,H.263,MPEG-4,H.264,H.265
  • Scalable Video Coding and Multiview Coding
  •  

Exam

oral

Course Material

available on stud.IP

Literature

Gonzalez, R.; Woods, E.: Digital Image Processing, Prentice Hall 2008
Jähne, B.: Digitale Bildverarbeitung, 5. Auflage, Springer-Verlag, 2002

Ohm, J.-R.: Digitale Bildcodierung. Springer-Verlag, 1995
Ohm, J.-R.: Multimedia Communications Technology. Springer-Verlag, 2004
Jayant, N. S.; Noll, P.: Digital Coding of Waveforms. Principles and Applications to Speech and Video. Prentice Hall, 1984
Wang, Y.; et. al.: Video Processing and Communications. Prentice Hall, 2002
Rao, K. R.; et. al.: The transform and data compression handbook. CRC Press, 2001
Rao, K.R.: Techniques & Standards for Image, Video & Audio Coding, Prentice Hall 1996
Watkinson: MPEG-2, Focal Press, 1999
Barnsley, M. F.; Hurd, L. P.: Fractal Image Compression, AK Peters, 1993
Pennebaker, W. B.; et. al.: JPEG Still Compression Standard, New York, 1993
Taubman, D. S.; et. al.: JPEG2000, Kluwer Academics Publishers, 2002
Richardson, I. E. G.: H.264 and MPEG 4 Video Compression, J. Wiley & Sons, Ltd., 2003
Vetterli, M.; Kovacevic, J.: Wavelets and Subband Coding. Prentice Hall, 1995
Gersho, A.; Gray, R. M.: Vector Quantization and Signal Compression. Kluwer, 1992

 

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