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A learning-by-example method for reducing BDCT compression artifacts in high-contrast images.

Wang, Guangyu. / Thesis submitted in: December 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 70-75). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- BDCT Compression Artifacts --- p.1 / Chapter 1.2 --- Previous Artifact Removal Methods --- p.3 / Chapter 1.3 --- Our Method --- p.4 / Chapter 1.4 --- Structure of the Thesis --- p.4 / Chapter 2 --- Related Work --- p.6 / Chapter 2.1 --- Image Compression --- p.6 / Chapter 2.2 --- A Typical BDCT Compression: Baseline JPEG --- p.7 / Chapter 2.3 --- Existing Artifact Removal Methods --- p.10 / Chapter 2.3.1 --- Post-Filtering --- p.10 / Chapter 2.3.2 --- Projection onto Convex Sets --- p.12 / Chapter 2.3.3 --- Learning by Examples --- p.13 / Chapter 2.4 --- Other Related Work --- p.14 / Chapter 3 --- Contamination as Markov Random Field --- p.17 / Chapter 3.1 --- Markov Random Field --- p.17 / Chapter 3.2 --- Contamination as MRF --- p.18 / Chapter 4 --- Training Set Preparation --- p.22 / Chapter 4.1 --- Training Images Selection --- p.22 / Chapter 4.2 --- Bit Rate --- p.23 / Chapter 5 --- Artifact Vectors --- p.26 / Chapter 5.1 --- Formation of Artifact Vectors --- p.26 / Chapter 5.2 --- Luminance Remapping --- p.29 / Chapter 5.3 --- Dominant Implication --- p.29 / Chapter 6 --- Tree-Structured Vector Quantization --- p.32 / Chapter 6.1 --- Background --- p.32 / Chapter 6.1.1 --- Vector Quantization --- p.32 / Chapter 6.1.2 --- Tree-Structured Vector Quantization --- p.33 / Chapter 6.1.3 --- K-Means Clustering --- p.34 / Chapter 6.2 --- TSVQ in Artifact Removal --- p.35 / Chapter 7 --- Synthesis --- p.39 / Chapter 7.1 --- Color Processing --- p.39 / Chapter 7.2 --- Artifact Removal --- p.40 / Chapter 7.3 --- Selective Rejection of Synthesized Values --- p.42 / Chapter 8 --- Experimental Results --- p.48 / Chapter 8.1 --- Image Quality Assessments --- p.48 / Chapter 8.1.1 --- Peak Signal-Noise Ratio --- p.48 / Chapter 8.1.2 --- Mean Structural SIMilarity --- p.49 / Chapter 8.2 --- Performance --- p.50 / Chapter 8.3 --- How Size of Training Set Affects the Performance --- p.52 / Chapter 8.4 --- How Bit Rates Affect the Performance --- p.54 / Chapter 8.5 --- Comparisons --- p.56 / Chapter 9 --- Conclusion --- p.61 / Chapter A --- Color Transformation --- p.63 / Chapter B --- Image Quality --- p.64 / Chapter B.1 --- Image Quality vs. Quantization Table --- p.64 / Chapter B.2 --- Image Quality vs. Bit Rate --- p.66 / Chapter C --- Arti User's Manual --- p.68 / Bibliography --- p.70

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324812
Date January 2004
ContributorsWang, Guangyu, Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, x, 75 leaves : ill. (some col.) ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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