Progressive Lossless Image Coding and Transmission Using Edge Adaptive Hierarchical Interpolation
- 주제(키워드) pyramid data structure , image interpolation , lossless image compression , progressive image transmission
- 발행기관 아주대학교
- 발행년도 2012
- 학위수여년월 2012. 2
- 학위명 박사
- 학과 및 전공 일반대학원 컴퓨터공학과
- 실제URI http://www.dcollection.net/handler/ajou/000000012322
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
In this thesis, for the application of progressive lossless image coding and transmission, we proposed a new image interpolation algorithm called Edge Adaptive Hierarchical INTerpolation (EAHINT). We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the New Interleaved Hierarchical Interpolation (NIHINT) method, which is recognized as a superior pyramid data structure for progressive lossless image compression and transmission. Experimental results show that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality in progressive image transmission.
more목차
Chapter 1: Introduction 1
1.1 The Need of Lossless Image Compression 3
1.2 The Need of Progressive Image Compression and Transmission 3
1.3 Types of Progressive Image Coding and Transmission 4
1.4 Organization of the Thesis 7
Chapter 2: Preliminaries to Digital Image Compression 8
2.1. The Nature of Digital Images 8
2.2. Measuring Information: Shannon’s Information Theory 11
2.3. Image Data Redundancy and the Need of Image Compression 15
2.3.1. Coding Redundancy 16
2.3.2. Inter-pixel Redundancy (Source Redundancy) 18
2.3.3. Psychovisual Redundancy 20
2.3.4. Spectral Redundancy between Color Bands in color images 21
2.4. Image Compression Model 23
2.5. Performance Measurement of Digital Image Compression Techniques 27
Chapter 3: Related Work 29
3.1. An Overview of Multi-resolution Image Representation 29
3.2. Pyramid Data Structures for Progressive Image Coding 30
3.2.1 The HINT Algorithm 35
3.2.2 The IHINT Algorithm 36
3.2.3 The NIHINT Algorithm 36
3.2.4 Weakness of the HINT, IHINT and NIHINT Interpolating Algorithms 38
Chapter 4 : Edge Adaptive Hierarchical Interpolation 39
4.1. One-Directional Interpolator 47
4.2. Non-Directional Static Weighting Linear Interpolator 49
4.3. Multi-Directional Adaptive Weighting Interpolator 50
Chapter 5: Experimental Results and Discussion 53
5.1 Total Lossless Compression Bit Rate 55
5.2 Rate Distortion and Visual Quality at Intermediate Levels 59
Chapter 6 : Conclusion 63
