Ci Wang

Frame Rate Up-Conversion Using Trilateral Filtering

Frame rate up-conversion (FRUC) can enhance the visual quality of low frame rate video presented on liquid crystal display. To minimize the difference between a reference block and an interpolated block, an effective FRUC algorithm partitions a large block into several sub-blocks of smaller size and estimates their motions. Motion estimation searches for the block which has the minimum difference (cost) with the processed block in terms of some block matching distortion and motion discontinuity. As convexity and convergence of the cost function are not guaranteed, the computational cost for such motion estimation is usually extensive or unpredictable. In our proposed FRUC method, the two predictions of a frame to be interpolated are generated through shifting its nearest neighbor frames in the previous and following directions with the motion vectors estimated between them. The initial interpolated frame and its pixels reliability are subsequently estimated from these two predictions. We then apply a trilateral filter on the initial prediction to correct the unreliable pixels and to restore the missing pixels. Our proposed method not only reduces the computation for refining motion vectors, but also suppresses the interpolation noises and misregistration errors. We have conducted extensive experiments and the results show that the proposed algorithm outperforms the existing methods with better objective and subjective visual quality, and achieves about 3 dB on-average peak signal-to-noise ratio improvement.

Down-Sampling Based Video Coding Using Super-Resolution Technique

It has been reported that oversampling a still image before compression does not guarantee a good image quality. Similarly, down-sampling before video compression in low bit rate video coding may alleviate the blocking effect and improve peak signal-to-noise ratio of the decoded frames. When the number of discrete cosine transform coefficients is reduced in such a down-sampling based coding (DBC), the bit budget of each coefficient will increase, thus reduce the quantization error. A DBC video coding scheme is proposed in this paper, where a super-resolution technique is employed to restore the down-sampled frames to their original resolutions. The performance improvement of the proposed DBC scheme is analyzed at low bit rates, and verified by experiments.

Adaptive reduction of blocking artifacts in DCT domain for highly compressed images

A major drawback of block discrete cosine transform-based compressed image is the appearance of visible discontinuities along block boundaries in low bit-rate coding, which are commonly referred as blocking artifacts. Reduction of blocking artifacts can significantly improve image quality and extend maximum compression ratio under certain subjective quality. In this paper, a method for blind measuring the degree of blocking artifacts and postprocessing technology for removing these discontinuities are proposed, and it is most important that all these works are operated in DCT domain. By Walsh transform and local threshold technology, the precision of edge detection by Sobel operator is improved, so blurring in objective edge is reduced. In the process of deblocking, compensatory coefficients matrices and adaptive smooth method are introduced to improve postprocessed image performance. Experiments demonstrate that the combination of all these methods gives excellent results compared with other approaches before in both subjective and objective viewpoints.

Improved Super-Resolution Reconstruction From Video

Super-resolution (SR) reconstruction usually consists of four steps: registration, interpolation, restoration, and postprocessing. The registration precision (RP) and the initial SR image estimation (ISIE) greatly influence the quality of reconstructed images. A scheme to enhance RP and ISIE is proposed in this paper. Before the registration, each video frame is iteratively upsampled, the registration from current SR reconstructed frame and its adjacent upsampled frames are then estimated, and adjacent frames are warped with registrations to form the high-definition (HD) constraint set, while input frames are used to construct the low-definition (LD) constraint set. The SR reconstructed image corresponds to the minimum difference with the HD constraint set, and its warped and downsampled form corresponds to the minimum difference with the LD constraint set. ISIE can thus be improved from the HD constraint set. In this scheme, the outlier registration with the HD pixel precision is obtained by comparing warped HD frames with the reconstructed SR image, and the adverse influence can be eliminated in calculating LD difference to accelerate the convergence rate of the SR reconstruction and improve the quality of reconstructed images. The performance improvement of the proposed scheme over some existing work is shown in experimental results

Fast Edge-Preserved Postprocessing for Compressed Images

Images are often coded using block-based discrete cosine transform (DCT), where blocking and ringing artifacts are the most common visual distortion. In this letter, a fast algorithm is proposed to alleviate the said artifacts in the DCT domain. The new concept is to decompose a row or column image vector to a gradually changed signal and a fast variational signal, which correspond to low-frequency (LF) and high-frequency (HF) DCT subbands, respectively. Blocking artifacts between adjacent LF blocks are suppressed by smoothing LF components and discarding invalid HF ones, and ringing artifacts inside HF vectors are reduced by a simplified bilateral filter. With such a process, edges are preserved while blockiness and ringing are alleviated. Analytic and experimental results confirm the robustness and computational efficiency of the proposed method

Adaptive non-local means filter for image deblocking

In this paper, a novel deblocking algorithm is proposed to remove the blocking artifacts in images compressed by block discrete cosine transform (BDCT), using an adaptive non-local means filter. We prefer block as the basic processing unit, whose estimation is obtained as a weighted sum of neighborhood blocks. The weights are defined as a multivariate Gaussian with a covariance matrix that depends on the difference between the quantization noise of the block and that of its neighborhood blocks. The weights react adaptively to both block content and quantization noise intensity. Extensive experimental results and comparative studies are proposed to demonstrate the effectiveness of the proposed deblocking algorithm.

Down-sampling based video coding with super-resolution technique

It has been proven that performance of video coding at low bit rates can be improved by down-sampling a video before compression and up-sampling it after decompression. The down-sampling based coding (DBC) provides more bit budget for DCT coefficients, which preserve more high order coefficients. In this paper we propose a new DBC which uses a modified example-based super-resolution (SR) algorithm to restore the original resolution of down-sampled video signals. Experiments have shown the proposed scheme achieve PSNR improvement and better visual quality at low bit rates as compared with the H.264/AVC video coding, as well as the DBC using a general locally linear embedding (LLE) method as in [1].

A highly efficient, low delay architecture for transporting H.264 video over wireless channel

Transporting hybrid coded video over wireless channel is very challenging. On the one hand, wireless link is much more error prone than wired network due to time varying channel conditions such as fading and multipath interference. On the other hand, hybrid coded video is very vulnerable to error propagation when transmitted over error prone channels. Numerous researches have been conducted to enhance error robustness for wireless video transmission. Among them, many schemes use retransmission to reduce packet loss rate and improve reconstructed video quality. However, retransmission is delay constrained due to the low delay nature of real-time video. Packet loss is inevitable even when retransmission is employed. In the proposed architecture, a novel error recovery scheme is introduced which switches adaptively between ACK and NACK modes according to channel conditions. Video proxy server at the base station is designed to make the retransmission and feedback based error recovery method more effective. State-of-the-art H.264 is used as video encoder since it provides not only high coding efficiency but also multi-frame which plays a key role in the framework. Simulation results demonstrate the effectiveness of this architecture.

Reconstructing Videos From Multiple Compressed Copies

A single source video may be compressed using different encoders with different settings. In the context of online video sharing, many such video copies exist, and an end user may have access to a few of them and would like to reconstruct a video sequence with quality superior to all available copies. In this paper, we propose a scheme to improve the video quality by projecting the reconstructed video onto the quantization constraint sets defined by multiple video copies. Experimental results show that the proposed method is capable of improving video quality both subjectively and objectively.

A novel scalable video coding scheme using super resolution techniques

A novel scheme of scalable video coding (SVC) using super-resolution techniques is proposed in this paper. Utilizing the spatial/temporal scalability of H.264/AVC, we encode half of input high-resolution(HR) frames and their low-resolution (LR) counterparts in a video sequence and employ super-resolution (SR) method to reconstruct skipped frames during decoding. The payload saved from skipped frames can be used to improve the quality of encoded frames. This scheme provides a choice of SVC to improve the quality of HR frames while maintaining low bit rate transmission and reducing encoding complexity. Experiments show that our scheme performs well in both peak signal to noise ratio (PSNR) and subjective visual quality at low bit rate.