Digital Coding of Waveforms

The use of variable block-size motion estimation (ME), disparity estimation (DE), and multiple reference frames selection aims to improve the coding efficiency of multiview video coding (MVC), however, this is at the cost of high computational complexity of these advanced coding techniques, which are not suitable for real-time video broadcasting applications. In this paper, we propose an efficient ME and DE algorithm for reducing the computational complexity of MVC. Firstly, according to the characteristics of the coded block pattern and rate distortion (RD) cost, an early DIRECT mode decision algorithm is proposed. Then, based on the characteristics of the initial search point in the ME/DE process and the observation that the best point is center-biased, an early ME/DE termination strategy is proposed. If the ME/DE early termination is not satisfied, the ME/DE search window will be reduced by applying the optimal theory. At last, two block matching search strategies are proposed to predict the best point for the ME/DE. Experimental results show that the proposed algorithm can achieve 50.05% to 77.61%, 64.83% on average encoding time saving. Meanwhile, the RD performance degradation is negligible. Especially, the proposed algorithm can be applied to not only the odd views but also the even views.

Efficient Motion and Disparity Estimation Optimization for Low Complexity Multiview Video Coding

Perceptual quality assessmentplays a vital role in the visual communication systems owing to theexistence of quality degradations introduced in various stages of visual signalacquisition, compression, transmission and display.Quality assessment for visual signals can be performed subjectively andobjectively, and objective quality assessment is usually preferred owing to itshigh efficiency and easy deployment. A large number of subjective andobjective visual quality assessment studies have been conducted during recent years.In this survey, we give an up-to-date and comprehensivereview of these studies.Specifically, the frequently used subjective image quality assessment databases are firstreviewed, as they serve as the validation set for the objective measures.Second, the objective image quality assessment measures are classified and reviewed according to the applications and the methodologies utilized in the quality measures.Third, the performances of the state-of-the-artquality measures for visual signals are compared with an introduction of theevaluation protocols.This survey provides a general overview of classical algorithms andrecent progresses in the field of perceptual image quality assessment.

Perceptual image quality assessment: a survey

We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal information for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-the-art deghosting schemes. 1 1 The MATLAB code of the proposed algorithm will be made available online. Preliminary results of Section III-A [1] were presented at the IEEE International Conference on Image Processing, Canada, 2015.

Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

The high definition (HD) and ultra HD videos can be widely applied in broadcasting applications. However, with the increased resolution of video, the volume of the raw HD visual information data increases significantly, which becomes a challenge for storage, processing, and transmitting the HD visual data. The state-of-the-art video compression standard-H.265/High Efficiency Video Coding (HEVC) compresses the raw HD visual data efficiently, while the high compression rate comes at the cost of heavy computation load. Hence, reducing the encoding complexity becomes vital for the H.265/HEVC encoder to be used in broadcasting applications. In this paper, based on the best motion vector selection correlation among the different size prediction modes, we propose a fast motion estimation (ME) method to reduce the encoding complexity of the H.265/HEVC encoder. First, according to the prediction unit (PU) partition type, all PUs are classified into two classes, parent PU and children PUs, respectively. Then, based on the best motion vector selection correlation between the parent PU and children PUs, the block matching search process of the children PUs is adaptively skipped if their parent PU chooses the initial search point as its final optimal motion vector in the ME process. Experimental results show that the proposed method achieves an average of 20% ME time saving as compared with the original HM-TZSearch. Meanwhile, the rate distortion performance degradation is negligible.

Fast Motion Estimation Based on Content Property for Low-Complexity H.265/HEVC Encoder

The increasing popularity of video (i.e., audio-visual) applications or services over both wired and wireless links has prompted recent growing interests in the investigations of quality of experience (QoE) in online video transmission. Conventional video quality metrics, such as peak-signal-to-noise-ratio and quality of service, only focus on the reception quality from the systematic perspective. As a result, they cannot represent the true visual experience of an individual user. Instead, the QoE introduces a user experience-driven strategy which puts special emphasis on the contextual and human factors in addition to the transmission system. This advantage has raised the popularity and widespread usage of QoE in video transmission. In this paper, we present an overview of selected issues pertaining to QoE and its recent applications in video transmission, with consideration of the compelling features of QoE (i.e., context and human factors). The selected issues include QoE modeling with influence factors in the end-to-end chain of video transmission, QoE assessment (including subjective test and objective QoE monitoring) and QoE management of video transmission over different types of networks. Through the literature review, we observe that the context and human factors in QoE-aware video transmission have attracted significant attentions since the past two to three years. A vast number of high quality works were published in this area, and will be highlighted in this survey. In addition to a thorough summary of recent progresses, we also present an outlook of future developments on QoE assessment and management in video transmission, especially focusing on the context and human factors that have not been addressed yet and the technical challenges that have not been completely solved so far. We believe that our overview and findings can provide a timely perspective on the related issues and the future research directions in QoE-oriented services over video communications.

QoE in Video Transmission: A User Experience-Driven Strategy

Color-to-gray (C2G) image conversion is the process of transforming a color image into a grayscale one. Despite its wide usage in real-world applications, little work has been dedicated to compare the performance of C2G conversion algorithms. Subjective evaluation is reliable but is also inconvenient and time consuming. Here, we make one of the first attempts to develop an objective quality model that automatically predicts the perceived quality of C2G converted images. Inspired by the philosophy of the structural similarity index, we propose a C2G structural similarity (C2G-SSIM) index, which evaluates the luminance, contrast, and structure similarities between the reference color image and the C2G converted image. The three components are then combined depending on image type to yield an overall quality measure. Experimental results show that the proposed C2G-SSIM index has close agreement with subjective rankings and significantly outperforms existing objective quality metrics for C2G conversion. To explore the potentials of C2G-SSIM, we further demonstrate its use in two applications: 1) automatic parameter tuning for C2G conversion algorithms and 2) adaptive fusion of C2G converted images.

Objective Quality Assessment for Color-to-Gray Image Conversion

A novel frame-level rate control (RC) algorithm is presented in this paper for temporal scalability of scalable video coding. First, by introducing a linear quality dependency model, the quality dependency between a coding frame and its references is investigated for the hierarchical B-picture prediction structure. Second, linear rate-quantization (R-Q) and distortion-quantization (D-Q) models are introduced based on different characteristics of temporal layers. Third, according to the proposed quality dependency model and R-Q and D-Q models for each temporal layer, adaptive weighting factors are derived to allocate bits efficiently among temporal layers. Experimental results on not only traditional quarter common intermediate format/common intermediate format but also standard definition and high definition sequences demonstrate that the proposed algorithm achieves excellent coding efficiency as compared to other benchmark RC schemes.

Rate Control Optimization for Temporal-Layer Scalable Video Coding

To improve compression performance, High Efficiency Video Coding (HEVC) employs a quad-tree based block representation, namely Coding Tree Unit (CTU), which can support larger partitions and more coding modes than a traditional macroblock. Despite its high compression efficiency, the number of combinations of coding modes increases dramatically, which results in high computational complexity at the encoder. Here we propose a flexible framework for HEVC coding mode selection, with a user-defined global complexity factor. Based on linear programming, a hierarchical complexity allocation scheme is developed to allocate computational complexities among frames and Coding Units (CUs) to maximize the overall Rate-Distortion (RD) performance. In each CU, with the allocated complexity factor, a mode mapping based approach is employed for coding mode selection. Extensive experiments demonstrate that, with a series of global complexity factors, the proposed model can achieve good trade-offs between computational complexity and RD performance.

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Flexible Mode Selection and Complexity Allocation in High Efficiency Video Coding

This paper proposes an efficient algorithm for fast mode decision in H.264/advanced video coding by adaptively predicting the optimal mode for each macroblock (MB) to be coded. Firstly, encoding modes are projected as points onto a 2-D map, and an optimal 2-D point of the MB to be coded is predicted based on the encoding information of spatial-temporal neighboring blocks. Then, a priority-based mode candidate list with a descending order to be the best mode is constructed based on the optimal 2-D point. Finally, mode decision is performed according to the priority-based mode candidate list in the checking order, from the most important mode to the least one, with early termination conditions. Extensive experimental results demonstrate that the proposed algorithm is superior to three recent fast mode decision algorithms, with the entire encoding time being reduced by about 60% for quarter common intermediate format/common intermediate format/standard-definition sequences on average and the rate distortion performance being kept almost intact.

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Tiesong Zhao

Papers

QoE in Video Transmission: A User Experience-Driven Strategy

Objective Quality Assessment for Color-to-Gray Image Conversion

Rate Control Optimization for Temporal-Layer Scalable Video Coding

Flexible Mode Selection and Complexity Allocation in High Efficiency Video Coding

Fast Mode Decision Based on Mode Adaptation