Improved Method for the Macroblock‐Level Deblocking Scheme

This paper presents a deblocking method for video compression in which the blocking artifacts are effectively extracted and eliminated based on both spatial and frequency domain operations. Firstly, we use a probabilistic approach to analyze the performance of the conventional macroblock‐level deblocking scheme. Then, based on the results of the analysis, an algorithm to reduce the computational complexity is introduced. Experimental results show that the proposed algorithm outperforms the conventional video coding methods in terms of computation complexity while coding efficiency is maintained.     

Image deblocking via sparse representation

Image compression based on block-based Discrete Cosine Transform (BDCT) inevitably produces annoying blocking artifacts because each block is transformed and quantized independently. This paper proposes a new deblocking method for BDCT compressed images based on sparse representation. To remove blocking artifacts, we obtain a general dictionary from a set of training images using the K-singular value decomposition (K-SVD) algorithm, which can effectively describe the content of an image. Then, an error threshold for orthogonal matching pursuit (OMP) is automatically estimated to use the dictionary for image deblocking by the compression factor of compressed image. Consequently, blocking artifacts are significantly reduced by the obtained dictionary and the estimated error threshold. Experimental results indicate that the proposed method is very effective in dealing with the image deblocking problem from compressed images.     

Adaptive deblocking method for low bitrate coded HEVC video

HEVC in-loop deblocking filter significantly improves the subjective quality of coded video by removing blocking artifact. However, there are still visible blocking artifacts in the complex videos with fast and chaotic motions coded at a low bitrate. In this paper, we propose a three-step deblocking filter scheme, which pre-processes video to remove undesired noise, next removes the corner outliers, and then suppresses the normal blocking artifacts with adaptive deblocking filters. The whole deblocking filtering process is applied on both luma and chroma components. Experimental results show that the proposed method could effectively improve the subjective quality for various videos, and outperform other typical post-processing deblocking methods.     

Variable block-based deblocking filter for H.264/AVC on low-end and low-bit rates terminals

H.264/AVC supports variable block motion compensation, multiple reference frames, 1/4-pixel motion vector accuracy, and in-loop deblocking filter, compared with previous video coding standards. While these coding techniques are major functions for video compression improvement, they lead to high computational complexity at the same time. For the H.264 video coding techniques to be actually applied on low-end/low-bit rates terminals more extensively, it is essential to improve the coding efficiency. Currently the H.264 deblocking filter, which can improve the subjective quality of video, is hardly used on low-end terminals due to computational complexity.In this paper, we propose an enhanced method of deblocking filter that efficiently reduces the blocking artifacts occurring during the low-bit rates video coding. In the ‘variable block-based deblocking filter (VBDF)’ proposed in this paper, the temporal and spatial characteristics of moving pictures are extracted using the variable block-size information of motion compensation, the filter mode is classified into four different modes according to the moving-picture characteristics, and the adaptive filtering is executed in the separate modes. The proposed VBDF can reduce the blocking artifacts, prevent excessive blurring effects, and achieve about 30–40% computational speedup at about the same PSNR compared with the existing methods.     

一种基于人类视觉系统的去块效应算法

基于块离散余弦变换的图像和视频压缩主要缺点就是在低比特率时会在块边界出现明显的方块效应。本文提出一种充分利用人类视觉特性,在图像的平滑区和纹理区分别采用一维DCT域滤波和空间域滤波的去块效应算法。实验结果表明该算法既能有效地去除方块效应又能保护图像的边缘信息。     

New Blocking Artifacts Reduction Method Based on Wavelet Transform

It is well known that a block discrete cosine transform compressed image exhibits visually annoying blocking artifacts at low-bit-rate. A new post-processing deblocking algorithm in wavelet domain is proposed. The algorithm exploits blocking-artifact features shown in wavelet domain. The energy of blocking artifacts is concentrated into some lines to form annoying visual effects after wavelet transform. The aim of reducing blocking artifacts is to capture excessive energy on the block boundary effectively and reduce it below the visual scope. Adaptive operators for different subbands are computed based on the wavelet coefficients. The operators are made adaptive to different images and characteristics of blocking artifacts. Experimental results show that the proposed method can significantly improve the visual quality and also increase the peak signal-noise-ratio（PSNR） in the output image.     

Automatic single-image-based rain streaks removal via image decomposition

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.     

Using edge direction information for measuring blocking artifacts of images

Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifacts measurement consistent with subjective rating.     

A new image quality assessment method to detect and measure strength of blocking artifacts

Block based transform coding is one of the most popular techniques for image and video compression. However it suffers from several visual quality degradation factors, most notably from blocking artifacts. The subjective picture quality degradation caused by blocking artifacts, in general, does not agree well with the popular objective quality measure such as PSNR.A new image quality assessment method that detects and measures strength of blocking artifacts for block based transform coded images is proposed. In order to characterize the blocking artifacts, we utilize two observations: if blocking artifacts occur on the block boundary, the pixel value changes abruptly across the boundary and the same pixel values usually span along the entire length of the boundary. The proposed method operates only on a single block boundary to detect blocking artifacts. When a boundary is classified as having blocking artifacts, corresponding blocking artifact strength is also computed. Average values of those blocking artifact strengths are converted into a single number representing the subjective image quality. Experiments on various JPEG compressed images with various bit rates demonstrated that the proposed blocking artifacts measuring value matches well with the subjective image quality judged by human observers.     

Image deblocking via shape-adaptive low-rank prior and sparsity-based detail enhancement

At low bit rates, visually annoying blocking artifacts are usually introduced in JPEG compressed images. In this paper, we proposed an image deblocking method combined with the shape-adaptive low-rank (SALR) prior, the quantization constraint (QC) prior and sparsity-based detail enhancement. We firstly design a deblocking model to obtain initial deblocked images under the maximum a posteriori (MAP) framework. More specifically, with the assumption of Gaussian quantization noise, the SALR prior is utilized to effectively separate signal from noise and preserve image edges. Compared with previous low rank priors, the SALR reconstructs a better result via shape adaptive blocks. The QC prior is also adopted to avoid over-smoothing and to enable a more accurate estimation. Finally, by extracting features of external images, the mapping matrix of sparse dictionary pairs is trained to enhance image details. Extensive experimental results demonstrate that the proposed deblocking method has superior performances in both subjective vision and objective quality.     

Low complexity deblocking method for DCT coded video signals

A new method to remove blocking artefacts in low bit-rate block-based video coding, such as MPEG-4 and H.264, is presented. A low computational deblocking filter with five modes is proposed, including three frequency-related modes (smooth mode, intermediate mode, and complex mode for low-frequency, mid-frequency, and high-frequency regions, respectively), one special mode (steep mode for a large offset between two blocks) and a refined mode (corner mode for the corner of four blocks). A mode decision procedure is also needed to decide which mode is given by observing pixel behaviour around the block boundary. To take the masking effect of the human visual system (HVS) into consideration, the filter for smooth mode is designed to be much stronger than that for complex mode, because human eyes are more sensitive to smooth regions. Experimental results show that, in most cases, the proposed algorithm removes more blocking artefacts than MPEG-4 deblocking filters do, and improves both subjective and objective image quality. The proposed algorithm keeps the computation lower than MPEG-4 and is suitable for most block-based image and video coding systems.     

一种基于多视点视频的低复杂度自适应环路滤波算法

自适应环路滤波(ALF)是面向高清的多视点视频编码(MVC)中的一项新的滤波技术,虽然能提高视频压缩的主观质量和客观质量,但是其复杂度过高阻碍了其实时应用。本文提出了一种低复杂度的ALF算法,充分利用了视点间相关性和层间相关性以减少亮度和色度分量的分割次数,并且能自适应跳过大部分帧的块控制(DBC)处理过程。实验结果表明,所提出的算法能在保证视频主观质量和客观质量基本不变的情况下减少61%左右的ALF处理时间。因此,所提出的方法在编码效率和复杂度上做到了很好的折中处理,并且能很好地改善ALF的性能。     

An automatic region-based video sequence codec based on fractal compression

In order to improve the performance of fractal video coding, we explore a novel fractal video sequences codec with automatic region-based functionality. To increase the quality of decoding image, intra frame coding, deblocking loop filter and sub-pixel block matching are applied to the codec. An efficient searching algorithm is used to increase the compression ratio and encoding speed. Automatic region-based fractal video sequences coding reduces coding stream greatly. Experimental results indicate that the proposed algorithm is more robust, and provides much less encoding time and bitrate while maintaining the quality of decompression image than the conventional CPM/NCIM method and other related references. We compare the proposed algorithm with three algorithms in Refs. [24], [25], [26], and the results of all these four algorithms are compared with H.264. The bitrate of the proposed algorithm is decreased by 0.11% and the other algorithms are increased by 4.29%, 6.85% and 11.62%, respectively. The average PSNR degradations of the four algorithms are 0.71 dB, 0.48 dB, 0.48 dB and 0.75 dB. So the bitrate of the proposed algorithm is decreased and the other algorithms are increased. At the meantime the compression time is reduced greatly, about 79.19% on average. The results indicate that, on average, the proposed automatic region-based fractal video sequences coding system can save compression time 48.97% and bitrate 52.02% with some image quality degradation in comparison with H.264, since they are all above 32 dB and the human eyes are insensitive to the differences.     

A locally adaptive algorithm for measuring blocking artifacts in images and videos

Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring image quality of a BDCT coded images or videos. It exhibits unique and useful features: (1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; (2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; (3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; (4) the quality measure is well defined in the range of 0–10. Experiments on various still images and videos show that the new quality measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.     

Improving MPEG-4 coding performance by jointly optimisingcompression and blocking effect elimination

In most current block-based image/video coding systems the compression stage and the deblocking stage operate separately and hence they cannot make use of each other to optimise the overall coding performance. It is suggested that the basic structure of the encoding systems should be modified such that the deblocking to be performed can be taken into account in the compression and the two processes can be jointly optimised. An example is also provided to show how this idea works successfully in an MPEG-4 codec to boost the rate-distortion performance when the suggested deblocking filter is exploited in the post-processing stage. The modification does not change the bit-stream format of the codec and hence is fully compatible with the original standard     

Design a deblocking filter with three separate modes in DCT-based coding

The reconstructed images from highly compressed data have noticeable image degradations, such as blocking artifacts near the block boundaries. Post-processing appears to be the most feasible solution because it does not require any existing standards to be changed. Markedly reducing blocking effects can increase compression ratios for a particular image quality or improve the quality of equally compressed images. In this work, a novel deblocking algorithm is proposed based on three filtering modes in terms of the activity across block boundaries. By properly considering the masking effect of the HVS (Human Visual System), an adaptive filtering decision is integrated into the deblocking process. According to three different deblocking modes appropriate for local regions with different characteristics, the perceptual and objective quality are improved without excessive smoothing the image details or insufficiently reducing the strong blocking effect on a flat region. According to the simulation results, the proposed method outperforms other deblocking algorithms in respect to PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural SIMilarity).     

Reduction of blocking effect in DCT-coded images based on a visual perception criterion

Blocking effect constitutes one of the main drawbacks of the actual DCT-based compression methods. We propose in this paper a new block reduction technique; it is based on a space-variant non-linear filtering operation of the blocking artifacts present in the image to be reconstructed. To account for the perceptual importance of the distortion, the amount of smoothing is adapted to the visibility of the blocking effect. A visibility parameter is computed for each artifact using the psychovisual properties of the human visual system (HVS). The postprocessing algorithm is in conformity with actual existing compression standards; it provides a way to greatly reduce the artifacts without degrading high-frequency information of the original image. First the proposed method is described and then experimental results are presented, showing the effectiveness of the correction.     

A generic post-deblocking filter for block based image compression algorithms

In this paper we propose a new post-processing deblocking technique that is independent of the compression method used to encode the image. The development of this filter was motivated by the use of Multidimensional Multiscale Parser (MMP) algorithm, a generic lossy and lossless compression method. Since it employs an adaptive block size, it presents some impairments when using the deblocking techniques presented in the literature. This led us to the development of a new and more generic deblocking method, based on total variation and adaptive bilateral filtering.The proposed method was evaluated not only for still images, but also for video sequences, encoded using pattern matching and transform based compression methods. For all cases, both the objective and subjective quality of the reconstructed images were improved, showing the versatility of the proposed technique.     

Segmentation of moving objects in image sequence: A review

Segmentation of objects in image sequences is very important in many aspects of multimedia applications. In second-generation image/video coding, images are segmented into objects to achieve efficient compression by coding the contour and texture separately. As the purpose is to achieve high compression performance, the objects segmented may not be semantically meaningful to human observers. The more recent applications, such as content-based image/video retrieval and image/video composition, require that the segmented objects be semantically meaningful. Indeed, the recent multimedia standard MPEG-4 specifies that a video is composed of meaningful video objects. Although many segmentation techniques have been proposed in the literature, fully automatic segmentation tools for general applications are currently not achievable. This paper provides a review of this important and challenging area of segmentation of moving objects. We describe common approaches including temporal segmentation, spatial segmentation, and the combination of temporal-spatial segmentation. As an example, a complete segmentation scheme, which is an informative part of MPEG-4, is summarized.     

H.263编码视频流的混合错误掩盖

当H．263编码视频流在因特网上传输时，易受错误的影响，错误不但会影响当前帧还会继续扩散到以后的解码帧，从而导致图像质量的严重恶化，目前消除错误影响的常用算法是空域掩盖和时域掩盖算法，但是单纯地使用空域算法会造成图像的钝化，而时域算法则无法处理大运动的图像区域，因此，建议了一种时域和空域混合掩盖算法，同时使用两类算法对发生错误的图像帧进行掩盖。模拟结果显示该算法能够达到可以接受的图像质量，适应于视频会议、远程教育等应用的要求。