Yunqiang Liu

Depth Image-Based Temporal Error Concealment for 3-D Video Transmission

A depth image-based error concealment algorithm for 3-D video transmission is proposed, which utilizes the strong correlations between 2-D video and its corresponding the depth map. We first investigate the internal characteristics of the macroblock in the depth map, and then take advantage of these characteristics to recover accurately the lost motion vector for the corrupted blocks, with the joint consideration of the neighbor information and the corresponding depth. Experimental results show that the proposed method provides significant improvements in terms of both objective and subjective evaluations.

A novel spatial and temporal correlation integrated based motion-compensated interpolation for frame rate up-conversion

In this paper, a novel motion-compensated interpolation (MCI) method for frame rate up-conversion based on spatial and temporal correlation integrated is presented. Comparing to conventional MCI method, there are four main advantages of the proposed algorithm. First, the motion vectors (MVs) embedded in the bit-stream are examined and corrected by the coding-type information, the spatial correlation in the MV field and the temporal correlation in the pixel field together. Second, constant motion velocity model based MV estimation for the blocks in the interpolated frame is used to gain the initial value with consideration of the correlation of the related MV. Third, further refinement on the estimated MVs is performed based on the spatial correlation in the interpolated frame and temporal correlation in the before and after frames together. Fourth, adaptive weighted bi-directional interpolation is applied to obtain final recovered pixels using the refined MVs. Experimental results show that the proposed algorithm achieves a significant increase on PSNR and also a great improvement of visual performance over the conventional method.

Adaptive frame recovery based on motion activity

Whole-frame loss of the compressed video is very common in transmission over error-prone networks since each coded picture is usually packetized into one single packet in order to reduce the bitstream overhead for transmission. In this paper we present an adaptive frame recovery algorithm which innovatively introduces the three-dimensional recursive search (3DRS) motion estimation method into fram reovr (FR), and dynamically selects between 3DRS based recovery and motion vector copy (MVC) based recovery according to the statistics of motion activity of previous frames. If the motion activity of the frame is large, we adopt 3DRS-based frame recovery. Otherwise MVC-based FR is used. For the former method, we first perform the modfief 3DRS to re-estimate the motion vectors (MVs) of the previous frame considering that the available motion information of previous frames is not close to the true motion trajectory. Then the MVs are extrapolated and refined as the MVs of the lost frame. The missing frame is recovered using motion compensation. For MVC-based FR, motion information of previous frames, derived from the decoder is reused. Experimental results show that our proposed solutions can achieve significant improvements in both PSNR and visual quality.

An Efficient Two-stage Error Detector Based on Syntax and Continuity

In video transmission, the compressed signal is extremely vulnerable to bit errors. Error concealment is widely used in video decoder to recover corrupted frames. Due to the use of variable length codes (VLCs), a single bit error in block-based bitstream may propagate to following of this slice. Especially, the effectiveness of error concealment technique relies heavily on correctly locating errors. In this paper, an error detector based on syntax and continuity which consists of two stages is proposed. The first stage is to find erroneous slice according to checking constraints imposed on video bitstream syntax or detecting special error patterns. In the second stage, the precise position of the first erroneous macroblock (MB) is found based on the continuity of spatial or temporal data of neighbor MBs. Simulation results demonstrate that the proposed method improves performance of error detection significantly compared with the traditional syntax-based method.

An improved DMVE temporal error concealment

During video transmission over error-prone networks, the compressed bit stream is often corrupted by channel errors which may cause the video quality degrading suddenly. In this paper, we present a novel temporal error concealment technique as a post-processing tool at the decoder side for recovering the lost information. In order to recover the lost motion vector, an improved decoder motion vector estimation (DMVE) criterion is introduced which considers temporal correlation and motion trajectory together. We utilize pixels in the two previous frames as well as surrounding pixels of the lost block. The best motion vector is determined according to the criterion, and then the lost pixels are recovered using motion compensation. Simulations show that the proposed technique can achieve remarkable objective (PSNR) and subjective gains in the quality of the recovered video.

Image Block Error Recovery Using Adaptive Patch_Based Inpainting

In this paper, we propose an adaptive patch-based inpainting algorithm for image block error recovery in block-based coding image transmission. The recovery approach is based on prior information - patch similarity within the image. In order to keep local continuity, we recover the lost pixels by copying pixel values from the source based on a similarity criterion according to the prior information. The pixel recovery is performed in a sequential fashion, such that in this manner, the recovered pixels can be used in the recovery process afterwards. In order to alleviate the error propagation with sequential recovery, we introduce an adaptive combination strategy which merges different directional recovered pixels according to the confidence of the estimated recovery performance. Experimental results show that the proposed method provides significant gains in both subjective and objective measurements for image block recovery.

Spatial error recovery using multi-directional inpainting

During transmission over error-prone networks, the compressed video signal may suffer a large drop in video quality for the block-based motion-compensation scheme. Error recovery is widely used in video decoders to reconstruct corrupted regions. In this paper, we propose a new spatial error recovery method utilizing multi-directional inpainting. It contains eight single-directional inpaintings which perform unsymmetrical matching to search for suitable information and keep local continuity. We also present a linear combination method which merges different directional matching patches to alleviate the error propagations. Experimental results show that the proposed method provides significant gains in both subjective and objective measurements.