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For an immersive visual communication experience, it is essential to enable technologies that can capture and transmit point clouds capable of accurately depicting a photorealistic impression. The MPEG standardization group has devised a method for compressing video-based point clouds called Video-based Point Cloud Compression (V-PCC). In the V-PCC process, it first projects a 3D point cloud onto 2D planes called 3D patch generation, consisting of normal estimation, initial segmentation, grid refine segmentation (GRS), and patch segmentation. Afterwards, the High-Efficiency Video Coding (HEVC) standard is utilized for 2D video compression. However, the GRS is the most time-consuming process in 3D patch generation; a state-of-the-art method has evolved to address this issue. In this paper, we propose an improved approach that eliminates redundant execution steps and speeds up the optimization process of GRS by predicting the convergence of the determined point cloud projection plane during iterations. Our experimental results show that our approach is more persuasive, reducing execution time by up to 15% with slight increases or decreases in the BD rate compared to the state-of-the-art method. [ABSTRACT FROM AUTHOR]

With the development of technology, the requirements of hardware equipment and user expectations of visual enjoyment are increasingly gradually. The Joint Video Exploration Team (JVET) has established the latest video compression standard, Future Video Coding (FVC). FVC adopts QuadTree plus Binary Tree (QTBT) based Coding Unit (CU) structure, which not only removes the complex hierarchical structure of the CU, Prediction Unit (PU), and Transform Unit (TU) but also supports square and rectangular coding blocks based on the texture of the video content. Although the QTBT structure can provide superior coding performance, it significantly increases the encoding time, particularly in intra coding. Therefore, developing a fast intra CU partition decision algorithm is essential. In this paper, a fast CU partition decision algorithm in FVC intra coding based on spatial features is proposed. Different spatial features in the pixel domain are proposed in the binary tree and quadtree decision processes. Spatial features for the binary tree are employed for early skipping of the encoding process of CUs with binary tree depth and for early determination of binary tree split mode. Spatial features for the quadtree are employed for early splitting or termination of CUs with quadtree depth. Compared with JEM 5.0, the proposed method can save 23% encoding time on average with a slight increase of 0.62% in the Bjontegaard delta bitrate (BDBR). [ABSTRACT FROM AUTHOR]

High-efficiency video coding (HEVC) utilizes a quadtree-structured coding unit (CU) for more possible sizes of basic blocks for later prediction. The exhaustive search for the optimal CU depth requires high complexity, which causes difficulties for real-time streaming. In the proposed method, we make use of the residual statistics of prediction units (PUs) in the current encoded CU to make a decision on CU early termination. The residual histogram is discussed, and the optimal early termination (ET) zone is designed; if the PU residual statistics fall in the ET zone, the early termination is triggered. The optimal parameters for the ET zone are solved and analyzed in the training stage, and can be estimated with table lookup and simple computations in the testing stage. Another early termination method using the neighboring SKIP information is also proposed. We use SKIP information from more meaningful CU neighbors defined and used in HEVC. We combine the proposed residual-based and SKIP-based algorithms with a state-of-the-art method. The experimental results show that compared to two state-of-the-art methods in both low delay (LP) and random access (RA) configurations, our preferred proposed combination can achieve the best BDBR results (0.737 % in LP and 0.471 % in RA) with a good corresponding TS performances (49.87 % in LP and 54.96 % in RA), making HEVC more suitable for real-time applications. [ABSTRACT FROM AUTHOR]

In this paper, a novel hardware-oriented color image compression algorithm based on digital halftoning and block truncation coding (BTC) techniques is proposed for very large-scale integration (VLSI) implementation. The proposed technique consists of a threshold generator, a bitmap generator, a BTC training module, a predictor, and a signed Golomb-Rice coding module. Because the wireless camera network is developed for perceiving, measuring, and collecting information from the environment, each camera sensing node should be designed to achieve low cost, small size, high compression rates, and low power consumption. Hence, a novel low-complexity, high-performance, transform-free, hardware-oriented color image compression algorithm based on digital halftoning and BTC is proposed. In order to achieve the performance of compressing images in real time, the proposed color image compression algorithm was realized by a VLSI technique. The VLSI architecture in this work contains only 8.1-k gate counts, and the core area is 81,000 μm2 synthesized using a TSMC 0.18-μm CMOS process. The operating frequency of this work is 100 MHz and consumes 2.91 mW, which is efficient to develop wireless electronic systems with the demand of color image compression in real time. Compared with JPEG- and JPEG-LS-based designs, this work reduces gate counts by at least 71.1 % and power consumption by 53 % and only requires a one-line-buffer memory. [ABSTRACT FROM AUTHOR]

We propose a fast coding unit (CU) depth decision algorithm in the High Efficiency Video Coding (HEVC) procedure based on statistical analysis. First, we derive a set of optimized weights of surrounding CU decisions to predict the current CU decision for 3 different Largest Coding Unit (LCU) classes. Second, for a given predicted current CU decision, we analyze the possible true current CU decisions, aiming to find the correspondence. A corresponding table is found and can be used to achieve target prediction accuracy. Third, for early termination of the encoding processes, the 3 early termination methods in a state-of-the-art work, as well as their different combinations, are evaluated. We show that using one of them is sufficient for saving time while encoding to keep the implementation complexity low. Compared with full CU search in HEVC standards, the proposed method reduces the encoding time by 57 and 49 % on average with Low Delay and Random Access profiles, respectively, with acceptable bitrate and PSNR performances. Compared with two state-of-the-art methods, the encoding time reduction is up to 23 and 13 % with Low Delay profile, 7 and 3 % with Random Access profile, on average, whereas the performances of bitrate and PSNR are similar. [ABSTRACT FROM AUTHOR]

In this paper, an application of sparse optimization in the error concealment area is proposed. The spatial and temporal formulations of the pixels in the current frame and reference frame are proposed to solve the problem. Based on the sparse characteristics of nature images, we form sparse optimization problems for both formulations. The optimization problem is solved by the primal-dual interior point method. The solutions are combined for better results. By solving for a limited numbers of significant predictors using the sparse optimization, our algorithm performs subjectively and objectively better for the concealed result; compared to two state-of-the-art spatial-temporal hybrid error concealment methods, the proposed methods can improve by up to 0.19 dB and 1.12 dB in PSNR (Peak Signal-to-Noise Ratio). [ABSTRACT FROM AUTHOR]

The proposed paper discusses two switching error concealment algorithms: SECA (Switching Error Concealment Algorithm) and OSECA (Optimal Switching Error Concealment Algorithm) to efficiently switch among three existing error concealment methods for optimal performance and complexity tradeoff. SECA uses the motion vector statistics in the neighborhood of the lost MB (Macro Block) to make the switching decision. SECA is better than the best-PSNR method by 0.14 dB in PSNR and better than the best-win-rate method by 1.49 % in win rate, with 63 % time complexity reduction. OSECA further considers the correlation between surrounding pixels of the lost MB and the pixels in the reference frame. An optimization problem is formulated to derive the optimal decision thresholds. For OSECA, the PSNR performance is further improved by 0.24 dB from SECA and the time complexity reduction from the existing work can increase to 69 %. On different testing sets of the lost MBs, the proposed SECA and OSECA perform consistently against existing methods. Compared to SECA in the testing sets, OSECA has larger PSNR improvement (by up to 0.23 dB) against the best-PSNR method, and has larger time complexity reduction (by up to 71 %) against existing method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel freeview generation system. We first discuss the problem of misalignment of the edges between color frame and depth frame, and propose an optimization method to solve it. Then an original frame is separated into two parts, depending on the sizes of the resulting dis-occluded areas in the virtual view. Illumination changes between current frame and the information from previous frames are modeled and compensated. In the virtual view, the missing pixels are recovered by the proposed inpainting method. Using depth information, we compute the priority of the recovering order among the missing pixels. The recovering process accounts for pixel consistency, and the process iterates between virtual color frame and depth frame. Experimental results show that, compared with a state-of-the-art work, the proposed method has better subjective and objective performances; the PSNR gain can be up to 2.9575 dB. [ABSTRACT FROM AUTHOR]