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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
81

Image splicing localization via semi-global network and fully connected conditional random fields

Cun, Xiao Dong January 2018 (has links)
University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science
82

A PC/AT-based ICT image archiving system.

January 1991 (has links)
by Ringo Wai-kit Lam. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1991. / Includes bibliographical references. / ACKNOWLEDGEMENTS / ABSTRACT / LIST OF FIGURES --- p.i / LIST OF TABLES --- p.iii / Chapter CHAPTER 1 --- INTRODUCTION --- p.1-1 / Chapter 1.1 --- Introduction --- p.1-1 / Chapter 1.2 --- Transform Coding Theory --- p.1-2 / Chapter 1.2.1 --- Image Transform Coder and Decoder --- p.1-2 / Chapter 1.2.2 --- Transformation --- p.1-4 / Chapter 1.2.3 --- Bit Allocation --- p.1-5 / Chapter 1.2.4 --- Quantization --- p.1-7 / Chapter 1.2.5 --- Entropy Coding --- p.1-8 / Chapter 1.2.6 --- Error of Transform Coding --- p.1-9 / Chapter 1.3 --- Organization of The Thesis --- p.1-10 / Chapter CHAPTER 2 --- 2D INTEGER COSINE TRANSFORM CHIP SET --- p.2-1 / Chapter 2.1 --- Introduction --- p.2-1 / Chapter 2.2 --- The Integer Cosine Transform (ICT) --- p.2-2 / Chapter 2.3 --- LSI Implementation --- p.2-4 / Chapter 2.3.1 --- ICT Chip --- p.2-4 / Chapter 2.3.2 --- Data Sequencer --- p.2-7 / Chapter 2.4 --- Design Considerations --- p.2-8 / Chapter 2.4.1 --- ICT chip --- p.2-9 / Chapter 2.4.1.1 --- Specifications --- p.2-9 / Chapter 2.4.1.2 --- I/O Bit Length Consideration --- p.2-10 / Chapter 2.4.1.3 --- Selection of The Transform Matrix --- p.2-12 / Chapter 2.4.2 --- Data Sequencer --- p.2-16 / Chapter 2.4.2.1 --- Normal Operation --- p.2-16 / Chapter 2.4.2.2 --- Low-pass Filtering Operation --- p.2-16 / Chapter 2.4.2.3 --- Subsampling Operation --- p.2-17 / Chapter 2.5 --- Architecture --- p.2-18 / Chapter 2.5.1 --- ICT chip --- p.2-18 / Chapter 2.5.1.1 --- Input Stage --- p.2-18 / Chapter 2.5.1.2 --- Control Block --- p.2-19 / Chapter 2.5.1.3 --- Multiplier --- p.2-19 / Chapter 2.5.1.4 --- Accumulator --- p.2-20 / Chapter 2.5.1.5 --- Output Stage --- p.2-21 / Chapter 2.5.2 --- Data Sequencer --- p.2-21 / Chapter 2.5.2.1 --- Input Stage --- p.2-22 / Chapter 2.5.2.2 --- Control Logic --- p.2-22 / Chapter 2.5.2.3 --- Internal Storage --- p.2-23 / Chapter 2.5.2.4 --- Output Stage --- p.2-24 / Chapter 2.6 --- 2D Integer Cosine Transform System --- p.2-24 / Chapter 2.6.1 --- Hardware Architecture --- p.2-24 / Chapter 2.6.2 --- Timing --- p.2-26 / Chapter 2.7 --- Conclusion --- p.2-27 / Chapter CHAPTER 3 --- A PC/AT-BASED IMAGE ARCHIVING SYSTEM --- p.3-1 / Chapter 3.1 --- Introduction --- p.3-1 / Chapter 3.2 --- Design Consideration --- p.3-1 / Chapter 3.2.1 --- Specifications --- p.3-2 / Chapter 3.2.1.1 --- Operations Supported --- p.3-2 / Chapter 3.2.1.2 --- Image Formats --- p.3-3 / Chapter 3.2.1.3 --- Software --- p.3-6 / Chapter 3.2.2 --- Storage Format of the Coded Image --- p.3-6 / Chapter 3.3 --- Hardware Architecture --- p.3-8 / Chapter 3.3.1 --- Input Stage --- p.3-11 / Chapter 3.3.2 --- Inverse Transform Address Generator --- p.3-11 / Chapter 3.3.3 --- Input Memory --- p.3-13 / Chapter 3.3.3.1 --- Address Map --- p.3-14 / Chapter 3.3.3.2 --- Bit Map --- p.3-14 / Chapter 3.3.3.3 --- Class Map --- p.3-15 / Chapter 3.3.4 --- ICT Processor --- p.3-15 / Chapter 3.3.5 --- Output Memory --- p.3-16 / Chapter 3.3.6 --- Address Generator --- p.3-16 / Chapter 3.3.6.1 --- Address Generator 1 (AG1) --- p.3-17 / Chapter 3.3.6.2 --- Address Generator 2 (AG2) --- p.3-21 / Chapter 3.3.6.3 --- Address Generator 3 (AG3) --- p.3-22 / Chapter 3.3.7 --- Control Register --- p.3-22 / Chapter 3.3.8 --- Interface Consideration --- p.3-23 / Chapter 3.3.9 --- Frame Buffer --- p.3-23 / Chapter 3.4 --- Software Structure --- p.3-23 / Chapter 3.4.1 --- Main Menu --- p.3-24 / Chapter 3.4.2 --- Forward Transform --- p.3-25 / Chapter 3.4.3 --- Inverse Transform --- p.3-25 / Chapter 3.4.3.1 --- Normal --- p.3-26 / Chapter 3.4.3.2 --- Subsampling --- p.3-26 / Chapter 3.4.3.3 --- Filtering --- p.3-26 / Chapter 3.4.3.4 --- Album --- p.3-27 / Chapter 3.4.3.5 --- Display and System --- p.3-28 / Chapter 3.5 --- Conclusion --- p.3-29 / Chapter CHAPTER 4 --- SYSTEM PERFORMANCE EVALUATION --- p.4-1 / Chapter 4.1 --- Introduction --- p.4-1 / Chapter 4.2 --- Result of Image Display --- p.4-1 / Chapter 4.3 --- Computation Time Requirement --- p.4-12 / Chapter 4.4 --- Comparison to Other Transform Chips and Image Transform Systems --- p.4-16 / Chapter 4.5 --- Conclusion --- p.4-20 / Chapter CHAPTER 5 --- CONCLUSION --- p.5-1 / Chapter 5.1 --- Further Development --- p.5-1 / Chapter 5.1.1 --- Employment of JPEG Scheme --- p.5-1 / Chapter 5.1.2 --- ICT Chip Set --- p.5-5 / Chapter 5.2 --- Summary of the Image Archiving System --- p.5-6 / Chapter CHAPTER 6 --- REFERENCES --- p.6-1 / Chapter CHAPTER 7 --- APPENDIX --- p.7-1
83

A hypercolumn based stereo vision model.

January 1993 (has links)
by Lam Shu Sun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves [91]-94). / Chapter Chapter1 --- Introduction: Binocular Depth Visual Perception of Human --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- The visual pathway --- p.2 / Chapter 1.3 --- The retina --- p.3 / Chapter 1.4 --- The ganglion cells --- p.5 / Chapter 1.5 --- The lateral geniculate nucleus --- p.7 / Chapter 1.6 --- The visual cortex --- p.8 / Chapter 1.6.1 --- The cortical cells --- p.8 / Chapter 1.6.2 --- The organization of the visual cortex --- p.9 / Chapter 1.7 --- Stereopsis --- p.11 / Chapter 1.7.1 --- Corresponding retinal points --- p.12 / Chapter 1.7.2 --- Binocular fusion --- p.14 / Chapter 1.7.3 --- The binocular depth cells --- p.14 / Chapter 1.8 --- Conclusion of chapter 1 --- p.15 / Chapter Chapter2 --- Computational Stereo Vision --- p.15 / Chapter 2.1 --- Stereo image geometry --- p.16 / Chapter 2.1.1 --- The crossed-looking geometry --- p.17 / Chapter 2.1.2 --- The parallel optical axes geometry --- p.19 / Chapter 2.2 --- The false targets problem --- p.20 / Chapter 2.3 --- Feature selection --- p.21 / Chapter 2.3.1 --- Zero-crossing method --- p.21 / Chapter 2.3.2 --- A network model for ganglion cell --- p.24 / Chapter 2.4 --- The constraints of matching --- p.28 / Chapter 2.5 --- Correspondence techniques --- p.29 / Chapter 2.6 --- Conclusion of chapter 2 --- p.29 / Chapter Chapter3 --- A Hypercolumn Based Stereo Vision Model --- p.30 / Chapter 3.1 --- A visual model for stereo vision --- p.30 / Chapter 3.2 --- The model of PSVM (A Computerized Visual Model) --- p.32 / Chapter 3.3 --- Local orientated line extraction (Stage 1 of PSVM) --- p.34 / Chapter 3.3.1 --- Orientated line detection network --- p.35 / Chapter 3.3.2 --- On-type orientated lines and off-type orientated lines --- p.37 / Chapter 3.4 --- Local line matching (Stage 2 of PSVM) --- p.38 / Chapter 3.4.1 --- Structure of hypercolumn in PSVM --- p.39 / Chapter 3.4.2 --- Line length discrimination model (Part of stage 2 of PSVM) --- p.41 / Chapter 3.4.3 --- Orientation-length detector --- p.42 / Chapter 3.4.4 --- Line length selection --- p.45 / Chapter 3.4.5 --- The matching model --- p.46 / Chapter 3.4.6 --- Fusional area in PSVM --- p.48 / Chapter 3.4.7 --- Matching mechanism --- p.49 / Chapter 3.4.8 --- Disparity detection --- p.50 / Chapter 3.5 --- Disparity integrations (Stage 3 of PSVM) --- p.53 / Chapter 3.5.1 --- The voter network --- p.54 / Chapter 3.5.2 --- The redistributor network --- p.55 / Chapter 3.6 --- Conculsion of chpater 3 --- p.57 / Chapter Chapter4 --- Implementation and Analysis --- p.58 / Chapter 4.1 --- The imaging geometry of PSVM --- p.58 / Chapter 4.2 --- Input --- p.59 / Chapter 4.3 --- The hypercolumn construction --- p.59 / Chapter 4.4 --- Analysis of matching mechanism in PSVM --- p.59 / Chapter 4.4.1 --- Fusional condition --- p.61 / Chapter 4.4.2 --- Disparity detection --- p.61 / Chapter 4.5. --- Matching rules in PSVM --- p.63 / Chapter 4.5.1 --- The ordering constraint --- p.63 / Chapter 4.5.2 --- The uniqueness constraint --- p.64 / Chapter 4.5.3 --- The figural continuity constraint --- p.64 / Chapter 4.5.4 --- The smoothness assumption --- p.65 / Chapter 4.6. --- Use multi-lengths of oriented line to solve the occlusion problem --- p.66 / Chapter 4.7 --- Performance of PSVM --- p.67 / Chapter 4.7.1 --- Artificial scene --- p.67 / Chapter 4.7.2 --- Natural images --- p.71 / Chapter 4.8 --- Discussion --- p.83 / Chapter 4.9 --- Overall conclusion --- p.83 / Appendix: Illustration example --- p.85 / References --- p.91
84

Tight frame based multi-focus image fusion with common degraded areas and upscaling via a single image. / CUHK electronic theses & dissertations collection

January 2013 (has links)
Wang, Tianming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 59-62). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.
85

From images to motion. / CUHK electronic theses & dissertations collection

January 1998 (has links)
by Siu-hang Or. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (p. 94-100). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.
86

3D model reconstruction with noise filtering using boundary edges.

January 2004 (has links)
Lau Tak Fu. / Thesis submitted in: October 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 93-98). / Abstracts in English and Chinese. / Chapter 1 - --- Introduction --- p.9 / Chapter 1.1 --- Scope of the work --- p.9 / Chapter 1.2 --- Main contribution --- p.11 / Chapter 1.3 --- Outline of the thesis --- p.12 / Chapter 2 - --- Background --- p.14 / Chapter 2.1 --- Three dimensional models from images --- p.14 / Chapter 2.2 --- Un-calibrated 3D reconstruction --- p.14 / Chapter 2.3 --- Self calibrated 3D reconstruction --- p.16 / Chapter 2.4 --- Initial model formation using image based --- p.18 / Chapter 2.5 --- Volumes from Silhouettes --- p.19 / Chapter 3 - --- Initial model reconstruct the problem with mismatch noise --- p.22 / Chapter 3.1 --- Perspective Camera Model --- p.24 / Chapter 3.2 --- "Intrinsic parameters, Extrinsic parameters and camera motion" --- p.25 / Chapter 3.2.1 --- Intrinsic parameters --- p.25 / Chapter 3.2.2 --- Extrinsic parameter and camera motion --- p.27 / Chapter 3.3 --- Lowe's method --- p.29 / Chapter 3.4 --- Interleave bundle adjustment for structure and motion recovery from multiple images --- p.32 / Chapter 3.5 --- Feature points mismatch analysis --- p.38 / Chapter 4 - --- Feature selection by using look forward silhouette clipping --- p.43 / Chapter 4.1 --- Introduction to silhouette clipping --- p.43 / Chapter 4.2 --- Silhouette clipping for 3D model --- p.45 / Chapter 4.3 --- Implementation --- p.52 / Chapter 4.3.1 --- Silhouette extraction program --- p.52 / Chapter 4.3.2 --- Feature filter for alternative bundle adjustment algorithm --- p.59 / Chapter 5 - --- Experimental data --- p.61 / Chapter 5.1 --- Simulation --- p.61 / Chapter 5.1.1 --- Input of simulation --- p.61 / Chapter 5.1.2 --- Output of the simulation --- p.66 / Chapter 5.1.2.1 --- Radius distribution --- p.66 / Chapter 5.1.2.2 --- 3D model output --- p.74 / Chapter 5.1.2.3 --- VRML plotting --- p.80 / Chapter 5.2 --- Real Image testing --- p.82 / Chapter 5.2.1 --- Toy house on a turntable test --- p.82 / Chapter 5.2.2 --- Other tests on turntable --- p.86 / Chapter 6 - --- Conclusion and discussion --- p.89
87

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

January 2004 (has links)
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
88

3D coarse-to-fine reconstruction from multiple image sequences.

January 2004 (has links)
Ip Che Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 119-127). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Previous Work --- p.2 / Chapter 1.2.1 --- Reconstruction for Architecture Scene --- p.2 / Chapter 1.2.2 --- Super-resolution --- p.4 / Chapter 1.2.3 --- Coarse-to-Fine Approach --- p.4 / Chapter 1.3 --- Proposed solution --- p.6 / Chapter 1.4 --- Contribution --- p.6 / Chapter 1.5 --- Publications --- p.7 / Chapter 1.6 --- Layout of the thesis --- p.7 / Chapter 2 --- Background Techniques --- p.8 / Chapter 2.1 --- Interest Point Detectors --- p.8 / Chapter 2.1.1 --- Scale-space --- p.9 / Chapter 2.1.2 --- Harris Corner detectors --- p.10 / Chapter 2.1.3 --- Other Kinds of Interest Point Detectors --- p.17 / Chapter 2.1.4 --- Summary --- p.18 / Chapter 2.2 --- Steerable filters --- p.19 / Chapter 2.2.1 --- Orientation estimation --- p.20 / Chapter 2.3 --- Point Descriptors --- p.22 / Chapter 2.3.1 --- Image derivatives under illumination change --- p.23 / Chapter 2.3.2 --- Image derivatives under geometric scale change --- p.24 / Chapter 2.3.3 --- An example of a point descriptor --- p.25 / Chapter 2.3.4 --- Other examples --- p.25 / Chapter 2.4 --- Feature Tracking Techniques --- p.26 / Chapter 2.4.1 --- Kanade-Lucas-Tomasi (KLT) Tracker --- p.26 / Chapter 2.4.2 --- Guided Tracking Algorithm --- p.28 / Chapter 2.5 --- RANSAC --- p.29 / Chapter 2.6 --- Structure-from-motion (SFM) Algorithm --- p.31 / Chapter 2.6.1 --- Factorization methods --- p.33 / Chapter 2.6.2 --- Epipolar Geometry --- p.39 / Chapter 2.6.3 --- Bundle Adjustment --- p.47 / Chapter 2.6.4 --- Summary --- p.50 / Chapter 3 --- Hierarchical Registration of 3D Models --- p.52 / Chapter 3.1 --- Overview --- p.53 / Chapter 3.1.1 --- The Arrangement of Image Sequences --- p.53 / Chapter 3.1.2 --- The Framework --- p.54 / Chapter 3.2 3 --- D Model Reconstruction for Each Sequence --- p.57 / Chapter 3.3 --- Multi-scale Image Matching --- p.59 / Chapter 3.3.1 --- Scale-space interest point detection --- p.61 / Chapter 3.3.2 --- Point descriptor --- p.61 / Chapter 3.3.3 --- Point-to-point matching --- p.63 / Chapter 3.3.4 --- Image transformation estimation --- p.64 / Chapter 3.3.5 --- Multi-level image matching --- p.66 / Chapter 3.4 --- Linkage Establishment --- p.68 / Chapter 3.5 --- 3D Model Registration --- p.70 / Chapter 3.6 --- VRML Modelling --- p.73 / Chapter 4 --- Experiment --- p.74 / Chapter 4.1 --- Synthetic Experiments --- p.74 / Chapter 4.1.1 --- Study on Rematching Algorithm --- p.74 / Chapter 4.1.2 --- Comparison between Affine and Metric transforma- tions for 3D Registration --- p.80 / Chapter 4.2 --- Real Scene Experiments --- p.86 / Chapter 5 --- Conclusion --- p.112 / Chapter 5.1 --- Future Work --- p.114 / Chapter A --- Camera Parameters --- p.116 / Chapter A.1 --- Intrinsic Parameters --- p.116 / Chapter A.2 --- Extrinsic Parameters --- p.117 / Bibliography --- p.127
89

Correspondence-free stereo vision.

January 2004 (has links)
by Yuan, Ding. / Thesis submitted in: December 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 69-71). / Abstracts in English and Chinese. / ABSTRACT --- p.i / 摘要 --- p.iii / ACKNOWLEDGEMENTS --- p.v / TABLE OF CONTENTS --- p.vi / LIST OF FIGURES --- p.viii / LIST OF TABLES --- p.xii / Chapter 1 --- INTRODUCTION --- p.1 / Chapter 2 --- PREVIOUS WORK --- p.5 / Chapter 2.1 --- Traditional Stereo Vision --- p.5 / Chapter 2.1.1 --- Epipolar Constraint --- p.7 / Chapter 2.1.2 --- Some Constraints Based on Properties of Scene Objects --- p.9 / Chapter 2.1.3 --- Two Classes of Algorithms for Correspondence Establishment --- p.10 / Chapter 2.2 --- Correspondenceless Stereo Vision Algorithm for Single Planar Surface Recovery under Parallel-axis Stereo Geometry --- p.13 / Chapter 3 --- CORRESPONDENCE-FREE STEREO VISION UNDER GENERAL STEREO SETUP --- p.19 / Chapter 3.1 --- Correspondence-free Stereo Vision Algorithm for Single Planar Surface Recovery under General Stereo Geometry --- p.20 / Chapter 3.1.1 --- Algorithm in Its Basic Form --- p.21 / Chapter 3.1.2 --- Algorithm Combined with Epipolar Constraint --- p.25 / Chapter 3.1.3 --- Algorithm Combined with SVD And Robust Estimation --- p.36 / Chapter 3.2 --- Correspondence-free Stereo Vision Algorithm for Multiple Planar Surface Recovery --- p.45 / Chapter 3.2.1 --- Plane Hypothesis --- p.46 / Chapter 3.2.2 --- Plane Confirmation And 3D Reconstruction --- p.48 / Chapter 3.2.3 --- Experimental Results --- p.50 / Chapter 3.3 --- Experimental Results on Correspondence-free Vs. Correspondence Based Methods --- p.60 / Chapter 4 --- CONCLUSION AND FUTURE WORK --- p.65 / APPENDIX --- p.67 / BIBLIOGRAPHY --- p.69
90

Edge-enhancing image smoothing.

January 2011 (has links)
Xu, Yi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 62-69). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Organization --- p.4 / Chapter 2 --- Background and Motivation --- p.7 / Chapter 2.1 --- ID Mondrian Smoothing --- p.9 / Chapter 2.2 --- 2D Formulation --- p.13 / Chapter 3 --- Solver --- p.16 / Chapter 3.1 --- More Analysis --- p.20 / Chapter 4 --- Edge Extraction --- p.26 / Chapter 4.1 --- Related work --- p.26 / Chapter 4.2 --- Method and Results --- p.28 / Chapter 4.3 --- Summary --- p.32 / Chapter 5 --- Image Abstraction and Pencil Sketching --- p.35 / Chapter 5.1 --- Related Work --- p.35 / Chapter 5.2 --- Method and Results --- p.36 / Chapter 5.3 --- Summary --- p.40 / Chapter 6 --- Clip-Art Compression Artifact Removal --- p.41 / Chapter 6.1 --- Related work --- p.41 / Chapter 6.2 --- Method and Results --- p.43 / Chapter 6.3 --- Summary --- p.46 / Chapter 7 --- Layer-Based Contrast Manipulation --- p.49 / Chapter 7.1 --- Related Work --- p.49 / Chapter 7.2 --- Method and Results --- p.50 / Chapter 7.2.1 --- Edge Adjustment --- p.51 / Chapter 7.2.2 --- Detail Magnification --- p.54 / Chapter 7.2.3 --- Tone Mapping --- p.55 / Chapter 7.3 --- Summary --- p.56 / Chapter 8 --- Conclusion and Discussion --- p.59 / Bibliography --- p.61

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