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

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