Xiuchang Zhu

Structural similarity optimal MB layer rate control for H.264

Conventional Rate Control (RC) schemes for video coding mostly take objective metric as distortion measurement, which can not achieve optimal subjective quality. This work applies Structural Similarity (SSIM) based subjective distortion to rate distortion optimization and RC in H.264, and proposes a SSIM optimal macroblock (MB) layer RC scheme. First, a SSIM quadratic distortion model is proposed based on extensive experiments and theoretical analysis. Then an improved quadratic Rate Quantization (R-Q) model is combined to obtain the solution of SSIM optimal MB layer quantization step (Qstep) by Lagrange multiplier method. Experimental results show that the proposed scheme preserves more image structural information and thus acquires better subjective quality compared with objective metric optimal MB layer RC JVT-O016 and classic JVT-G012.

Multi-Channel Mixed-Pattern Based Frame Rate Up-Conversion Using Spatio-Temporal Motion Vector Refinement and Dual-Weighted Overlapped Block Motion Compensation

In this paper, a novel motion compensated frame rate up-conversion (MC-FRUC) algorithm is proposed to enhance the visual quality of video sequences. First of all, the multi-channel mixed pattern (MCMP) is proposed to design a block matching criterion which uses a few computations to reveal the variances of one luminance channel and two chrominance channels in a video frame. Second, in basis of the forward and backward initial motion vector fields (MVFs) estimated by a variant of 3DRS algorithm, the spatio-temporal motion vector refinement (ST-MVR) algorithm is proposed to obtain the more smoother MVF by implicitly adding the spatio-temporal smooth constraint into the process of motion vector refinement, and then the highly fault-tolerant motion vector smoothing (HFT-MVS) algorithm is proposed to prevent the emergence of outliers in MVF. Finally, in order to reduce the edge blurring and occlusions, the proposed dual-weighted overlapped block motion compensation (DW-OBMC) algorithm uses the forward and backward MVFs to jointly produce the interpolated frame. Experimental results show that the proposed algorithm can significantly improve both objective and subjective quality of the interpolated frame with a low computational complexity, and provide the better performance than the existing algorithms.

Wyner-Ziv coding of video using compressive sensing without feedback channel

In this paper, we propose a novel Wyner-Ziv coding of video using compressive sensing (CS) without using feedback channel. Firstly, the proposed joint sparse model of inter frames is presented. Then, the CS based Wyner-Ziv (WZ) frame coding method is introduced. In proposed method, WZ frame is coded by block based CS measure, quantization, and entropy coding, with rate-distortion (RD) optimization through adaptive measurement collection. In order to obtain a better recover performance, WZ frame jointly reconstructed using side information (SI) based on inter-frame joint sparse representation at the decoder. Finally, experimental results are reported to demonstrate the effectiveness of the proposed coding method.

A low complexity MB layer rate control algorithm based on motion similarity for H.264

This paper presents a simple but effective macroblock (MB) layer rate control (RC) scheme for H.264/AVC with low complexity. First, to reduce computation cost and inaccuracy of linear mean absolute difference (MAD) prediction at MB layer adopted in JVT-G012, MAD is computed directly according to the difference between current original MB and the reference blocks pointed by estimated MV using intensive motion similarity. Then, MB header bits are predicted based on spatial-temporal correlation because it is not constant due to complicated coding modes and high compression efficiency of H.264. Finally, MB target bit rate is allocated according to its complexity and the parameters of quadratic R-D model are updated using coded MBs with high spatial-temporal correlation and motion similarity not the last coded data points. Simulation results show that the proposed scheme achieves an average PSNR gain of 0.37 dB, meets better with target bit rate, produces more consistent quality for the MBs in a frame and thus improves visual quality compared to classic JVT-H017 RC algorithm, simultaneously has lower computation complexity and suits for real-time application.

Image complexity adaptive intra-frame rate control algorithm for H.264/AVC

Aiming at the bad effect of intra-frame rate control (RC) of H.264, this paper proposed an image complexity adaptive intra-frame RC algorithm. First, in order to acquire intra-frame coding complexity more accurately, our algorithm analyzes intraframe by Sobel operator and establishes edge direction histogram for each 4×4 block, then gets the most probable intra prediction mode and corresponding reconstructed blocks, finally obtains the residual picture which is close to the actual coding residual. The mean absolute value of residual picture was used to represent the intra-frame coding complexity, combined with our empirical rate-quantization (R-Q) model and target bits allocation method from exhaustive experiments, and the intra QP was determined accurately. Extensive experimental results show that our algorithm not only obtains more accurate intra-frame output bitrate, more consistent subjective quality and more steady PSNR fluctuation compared with existing algorithm, but also prevents buffer overflow and frame skip effectively.

Simple and effective image quality assessment based on edge enhanced mean square error

Simple and effective image quality assessment (IQA) method is very desirable in many image and video processing applications, such as coding, transmission, restoration and enhancement. Classic pixel absolute error based objective IQA metrics such as mean square error (MSE) and corresponding peak signal to noise ratio (PSNR) are widely used for various applications due to low computation and clear physical meanings, but have also been criticized for poorly correlated with subjective evaluation. Inspired by that human visual system (HVS) is more sensitive to image local edge distortion than flat or texture areas, in this paper, we propose a novel edge enhanced MSE (EE-MSE) to emphasize edge distortion effects on IQA. Experimental results on LIVE database release 2 show that the proposed EE-MSE IQA metric is competitive with state-of-the-art HVS-based IQA metrics, while has lower computational complexity and is more suitable for optimization task.

Wyner-Ziv coding of image using compressed sensing

Compressed sensing (CS) is a technique for acquiring and reconstructing a signal utilizing the prior knowledge that it is sparse or compressible. In this paper, we present a Wyner-Ziv image coding framework, which combines the traditional image coding and compressed sensing. In our method, the image separate into two parts according to pixel location: the down-sampling image is encoded by traditional intra-frame coding and the rest part is encoded through CS method. In order to obtain a better recover performance, the whole image is jointly reconstructed using the two part data based on image sparse representation. The experimental results are reported to demonstrate the effectiveness of the proposed coding method.

Adaptive spatial error concealment algorithm selection framework using fuzzy classification

The error concealment (EC) technology attempt to recover the lost blocks by utilizing correlation block information (spatial or temporal). This paper introduces an adaptive spatial EC algorithm selection framework for block-based image/video coding systems. By using surrounding blocks information, fuzzy classifier can adaptively select the suitable EC method for each damaged block, and fuzzy rule are obtained from the labeled training image data. Our experimental results show that the proposed EC selection strategy obtains better subjective and objective quality.

A new human hand-image tracking method

Hand gesture recognition has been widely used in surveillance systems. And human hand image tracking is the foundation of the recognition, and it is also an important step. This paper proposes a new human hand tracking method in video surveillance based on color and shape. In the hand detection step, it proposes a detection method based on chromatic adaptive thresholding and the circular degree. In the hand tracking step, it uses a modified formula of SAD (Sum of Absolute Differences) to implement the matching method in order to track the hand. The results suggest that the method is accurate and simple. Additionally, this method also has lower computational complexity and it can be uses in most scenes.

Error concealment for stereoscopic images using mode selection

In this paper, a novel error concealment (EC) method for compressed stereoscopic image pairs is presented, which contains a new binocular EC mode and an improved monocular EC mode. The proposed algorithm selects appropriate EC mode to conceal the error block (EB) in the stereoscopic image according to the local characteristic of the EB. The experimental results demonstrate that the proposed scheme has good subjective and objective EC performance in stereoscopic images as compared to monocular mode.