Image coding based on vector quantization in vector transform domain

Pao Yue-kong Library Electronic Theses Database

Image coding based on vector quantization in vector transform domain


Author: Chan, Cheuk-fai
Title: Image coding based on vector quantization in vector transform domain
Degree: M.Sc.
Year: 1997
Subject: Image processing -- Digital techniques
Coding theory
Vector processing (Computer science)
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Dept. of Electronic Engineering
Pages: iii, 87 leaves : ill. ; 30 cm
Language: English
InnoPac Record:
Abstract: Image coding is an essential part of many applications such as digital television transmission, video conferencing, facsimile, image database, etc. There are many techniques to achieve this objective. The simplest technique is PCM which encodes individual pixels of an image in a memoryless way. Another technique is the Predictive coding. It quantizes the difference between a pixel and a prediction of the pixel from its neighbour pixels. In transform coding, a block of data samples is transformed from the image domain to the transform domain using an orthogonal transform, such as DCT. All of these techniques perform coding on scalars, either in image or transform domain. As Shannon's rate distortion theory [1] states that better performance can be achieved by coding vectors instead of scalars, many Vector Quantization (VQ) techniques have been developed. In 1991, a Vector Transform Vector Quantization (VTVQ) image coder was proposed by Li [4]. In his proposed VTVQ, image data vectors are first transformed into another set of vectors in the vector transform domain. VQ is then performed in the vector transform domain. The output of the vector transform domain VQ is transmitted or stored. At the reproduction end, a set of tables are used to reproduce quantized transform vectors. The corresponding inverse vector transform is used to reproduce the image. Similar to scalar transform coding, this vector transform coding techniques consists of two parts. The first part is the vector transform that has the decorrelation and energy packing properties. The second part is the VQ coding algorithm in vector transform domain. In this project, several new VTVQ image coding techniques are proposed and implemented. Their performance are also evaluated and summarized. Results show that all the proposed coders gain higher PSNR and better image quality than the Li's VTVQ coder for bpp higher than 0.25. When compared with the Li's VTVQ, the time and memory requirement for the codebook generation is largely reduced and the computation requirement for my proposed algorithms are also much superior than the Li's VTVQ algorithm.

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