論文研究了圖像及技頻信號的去躁技術，共分為四部分。第一部分研究了用來改進編碼的圖像的主觀同客觀賞質量的方法，介紹了兩個有效的圖像后處理技術。第二部分研究了基於貝葉斯估計鋒的對高斯噪聲圖像的去噪方法。第三部分介紹了對編碼的視頻信號去噪的兩個方法，這些方法可作為視頻環路和后處理濾波器，從而改進視頻信號的編碼性能。第四部分介紹了圖像邊緣檢測技術，該技術可結合基於於邊緣的圖像處理設術來改進含噪圖像的主觀同客觀質量。 / 第一部分，我們研究了一些用來改進編碼的圖像和視頻主觀同客觀質量的有效技術。採用基於塊的離散餘弦變換(DCT) 壓縮標準的圖像和視頻存在編碼效應。為了減少圖像的編碼效應，我們提出了一個基於綫性最小均值平方誤差(MMSE)標準的非局部Kuan (NLK) 濾波器。它被用來恢復量化后的DCT係數，然後我們提出了雙重量非局部Kuan (DNLK) 濾波器。這個DNLK濾波器用在過完備的DCTl係數，進一步形成了過完備雙重非局部Kuan (OCNLK) 濾波器。通過對一些使用測試用的量化表編碼的圖像， JPEG編碼的圖像的實驗，驗證了這兩种方法的有效性。 / 第二部分，我們採用了貝葉斯估計器來估計原始的變換域係數。該方法是對非局部Kuan (NLK) 濾波器的改進，它採用了高斯尺度混合模型來考慮變換域係數的非高斯特性。除去非局部估計的均值后的殘差係數並不是高斯分佈，所以我們採用了高斯混合模型來表示表示這些殘差係數。實驗給果證明了它在圖像去噪應用上的有效性，以及比NLK 濾波器更好的性能。 / 第三部分描述了用來改進視頻編碼性能的基於NLK 的方法。對於採用楨内/間預測和變換編碼的視頻而言，直接使用NLK濾波器將不能有效的去除編碼效應。我們分析了其中的原因，並提出了兩個視頻環路濾波器:基於四叉樹的NLK (QNLK) 濾波器和基於四叉樹的過完備NLK (QOCNLK) 濾波器。NLK 和過完備NLK濾波器用來恢復視頻殘差的量化係數。這些恢復后的係數進一步投射到所設計的量化約數集(QCS)裏。四叉樹技術用來進行自適應的濾波控制。實驗結果表明了相對于H.264/AVC HighProfile ，這些技術達到了可觀的比特率壓縮效率和視覺質量改善。我們同時也採用了QNLK和QOCNLK濾波器進行視頻后處理，並給出了實驗結果和分析。 / 第四部分，我們研究了一個基於非下採樣小波，使用三維隱馬爾可伕模型(HMM)的邊緣檢測技術。 提出的模型不僅能捕獲不同尺度間小波係數的關係，而且考慮了尺度内係數的依賴性。一個計算有效的最大似然(ML) 估計算法用來計算該模型的參數，每一個係數對應的隱含狀態用最大后騐(MAP) 估計來求得。基於一些自然圖像的實驗給果用來評償該算法。對於含噪圖像，該算法可以同時提取邊緣和去除噪聲信號。另外，提出的該模型對於其它的圖像視頻處理任務也是一個潛在的多尺度統計模型工具。 / The thesis investigates techniques to reduce noise in image and video signals.The investigation can be divided into four parts. The first part studies methods to improve the objective and subjective quality of coded images. The proposed two efficient image postprocessing techniques are presented. The second part investigates noise reduction of image signals corrupted by Gaussian noise and presents a denoising method based on Bayes estimator. The third part investigates noise reduction of coded videos by two different approaches. The approaches are used as video loop and postprocessing filters, in order to improve the coding performance of video signals. Finally, the fourth part investigates a new edge detection method that can provide an accurate detection of edges. The method can be used together with edge-based image processing techniques to improve objective and subjective quality of noisy images. / In the first part, the technique to improve the subjective and objective quality of coded images are studied. Coding artifacts exist in images using block-based discrete cosine transform (DCT) compression standards. In order to reduce image coding artifacts, a non-local Kuan's (NLK) filter is proposed from the minimum mean-square-error (MMSE) criterion. It is used to restore quantized DCT coefficients. Then we propose the dual non-local Kuan's (DNLK) filter by applying the NLK filter in dual-layer. The DNLK filter is further extended to form the overcomplete dual non-local Kuan's (OCDNLK) filter by applying to the overcomplete DCT coefficients. Experimental results on coded images using test quantization tables and JPEG coded images show the effectiveness of the two methods. / In the second part, we use a Bayes least square estimator to estimate the original transform coefficients optimally, from the Bayes perspective. It is an improved nonlocal Kuan's filter by considering non-Gaussian property of transform coefficients using Gaussian scale mixture model. The residual coefficients after subtracting non-local estimated means are not Gaussian distributed, so a Gaussian scale mixture model is employed to represent the residual coefficients. Experiments demonstrate its efficiency on image denoising and better performance than the NLK filter. / In the third part, the proposed methods based on the NLK filter to improve video coding performance are studied. Direct application of the NLK filter on videos coded using intra/inter-frame prediction and transform coding cannot improve coding performance efficiently. We identify the causes of the problem and propose quadtree-based NLK (QNLK) loop filter and quadtree-based overcomplete NLK (QOCNLK) loop filter to solve the problem. NLK and overcomplete NLK loop filters are used to restore quantized residual transform coefficients. Restored coefficients are then projected onto designed quantization constraint sets (QCS). Quadtree-based signaling strategy is used for adaptive filtering control. Experimental results show that the proposed loop filtering techniques achieve significant bit rate saving and visual quality improvement compared with H.264 or advanced video coding (AVC) High Profile. We also provide the experimental results and analysis of postprocessing application using QNLK and QOCNLK filters. / In the fourth part, a new edge detecting technique using 3-D Hidden Markov Model (HMM) based on the non-decimated wavelet is studied. The proposed model can not only capture the relationship of wavelet coefficients inter-scale, but also consider the intra-scale dependence. A computationally efficient maximum likelihood (ML) estimation algorithm is employed to compute parameters and the hidden state of each coefficient is revealed by maximum a posteriori (MAP) estimation. Experimental results of natural images are provided to evaluate the algorithm. For noisy images, the method can extract edges and remove noise simultaneously. The method can be used together with edge-based image processing techniques to improve subjective and objective quality of noisy images. In addition, the proposed model has the potential to be an efficient multi-scale statistical modeling tool for other image or video processing tasks. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhang, Renqi. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 109-113). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Dedication --- p.ii / Acknowledgments --- p.iii / Abstract --- p.viii / Publications --- p.x / Nomenclature --- p.xii / Contents --- p.xviii / List of Figures --- p.xxi / List o f Tables --- p.xxiii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.2 --- Thesis Outline --- p.4 / Chapter 2 --- Image/Video Coding Standard --- p.5 / Chapter 2.1 --- Image Coding Standard JPEG --- p.5 / Chapter 2.1.1 --- JPEG Codec --- p.6 / Chapter 2.1.2 --- Block-based Discrete Cosine Transform (DCT) --- p.7 / Chapter 2.1.3 --- Quant ization and Entropy Coding --- p.9 / Chapter 2.1.4 --- Decoding --- p.11 / Chapter 2.1.5 --- Effects of JPEG Compression --- p.12 / Chapter 2.2 --- Video Coding Standard H.264/AVC --- p.12 / Chapter 2.2.1 --- H.264 Codec --- p.14 / Chapter 2.2.2 --- Inter Prediction --- p.15 / Chapter 2.2.3 --- Intra Prediction --- p.15 / Chapter 2.2.4 --- Transform and Quantization --- p.17 / Chapter 2.2.5 --- Deblocking Filter --- p.19 / Chapter 2.3 --- Conclusion --- p.21 / Chapter 3 --- Image Postprocessing --- p.22 / Chapter 3.1 --- Introduction --- p.22 / Chapter 3.2 --- The Proposed Non-local KUAN's Filter in the DCT Domain --- p.24 / Chapter 3.2.1 --- LMMSE Filter in the DCT Domain --- p.25 / Chapter 3.2.2 --- The solution of the LMMSE Filter --- p.26 / Chapter 3.2.3 --- Non-local Parameter Estimation --- p.29 / Chapter 3.2.4 --- Investigation on Assumptions 1 and 2 --- p.29 / Chapter 3.3 --- Image Postprocessing by the Dual Non-local Kuan's Filter --- p.34 / Chapter 3.3.1 --- DNLK Filter --- p.35 / Chapter 3.3.2 --- OCDNLK Filter --- p.36 / Chapter 3.4 --- Experimental Results and Analysis --- p.37 / Chapter 3.4.1 --- Experiments on Three Test Quantization Tables --- p.37 / Chapter 3.4.2 --- Experiment al Setting --- p.38 / Chapter 3.4.3 --- Experiment al Results and Comparison with State-of-the-Art Methods --- p.38 / Chapter 3.4.4 --- Postprocessing on JPEG Coded Images --- p.40 / Chapter 3.4.5 --- Complexity Analysis --- p.40 / Chapter 3.5 --- Conclusion --- p.41 / Chapter 4 --- Improved Non-local Kuan's Filter using a Gaussian Scale Mixture --- p.49 / Chapter 4.1 --- Introduction --- p.49 / Chapter 4.1 --- Non-local Kuan's filter in the DCT domain --- p.50 / Chapter 4.1 --- Improved Non-local Kuan's Filter using a Guassian Scale Mixture --- p.52 / Chapter 4.3.1 --- Gaussian Scale Mixture Model --- p.52 / Chapter 4.3.2 --- Computation of Bayes Least Square Estimator --- p.55 / Chapter 4.4 --- Experimental Sett ings and Results --- p.56 / Chapter 4.5 --- Conclusion --- p.57 / Chapter 5 --- Quadtree-based Non-local Kuan's Filtering in Video Compression --- p.59 / Chapter 5.1 --- Introduction --- p.59 / Chapter 5.2 --- The Proposed Loop Filters --- p.62 / Chapter 5.2.1 --- Non-local Kuan's Filter --- p.62 / Chapter 5.2.2 --- The NLK Loop Filter --- p.65 / Chapter 5.2.3 --- The Overcomplete NLK Loop Filter --- p.67 / Chapter 5.2.4 --- Use of t he Quant ization Constraint Set (QCS) --- p.69 / Chapter 5.2.5 --- Performance of t he NLK and OCNLK Loop Filters for Video Coding --- p.70 / Chapter 5.2.6 --- The Proposed Quadtree-based NLK and OCNLK Loop Filters --- p.74 / Chapter 5.3 --- Experimental Result s and Analysis of QNLK and QOCNLK Loop Filters --- p.76 / Chapter 5.3.1 --- Experiment al Results of QNLK and QOCNLK Loop Filters --- p.76 / Chapter 5.3.2 --- Computational Complexity Analysis --- p.78 / Chapter 5.4 --- QNLK and QOCNLK Postprocessing Filters --- p.82 / Chapter 5.4.1 --- Experimental Result s and Analysis ofQNLK and QOCNLK Postprocessing Filters --- p.84 / Chapter 5.5 --- Conclusion --- p.85 / Chapter 6 --- Image Edge Detection using 3-D Hidden Markov Model based on the Non-decimated Wavelet --- p.88 / Chapter 6.1 --- Introduction --- p.88 / Chapter 6.2 --- Three-dimensional HMM based on the Non-decimated Wavelet (3-D N-WHMM) --- p.90 / Chapter 6.2.1 --- Hidden Markov Model (HMM) --- p.90 / Chapter 6.2.2 --- 3-D Hidden Markov Model (3-D HMM) --- p.91 / Chapter 6.2.3 --- Construction of the 3-D NWHMM --- p.92 / Chapter 6.2.4 --- Probabilistic Model for Individual Wavelet Coefficient --- p.92 / Chapter 6.2.5 --- Training Paramet ers and Searching for Hidden States --- p.94 / Chapter 6.3 --- Experimental Results and Analysis --- p.96 / Chapter 6.3.1 --- The algorithm implementation --- p.96 / Chapter 6.3.2 --- Comparisons with Canny and two multi-scalet echniques --- p.96 / Chapter 6.3.3 --- Experimental results of noisy images --- p.98 / Chapter 6.4 --- Conclusion --- p.98 / Chapter 7 --- Conclusions and Future Work --- p.103 / Chapter 7.1 --- Contributions of The Thesis --- p.103 / Chapter 7.2 --- Future Work and Research Directions --- p.104 / Chapter A --- Appendix A --- p.107 / Chapter A.1 --- Mathematical Derivations of equation (4.6) --- p.107 / Bibliography --- p.109
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328011 |
| Date | January 2012 |
| Contributors | Zhang, Renqi, Chinese University of Hong Kong Graduate School. Division of Electronic Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (xxiii, 113 leaves) : ill. (some col.) |
| Rights | Use 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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