A POCS-Based Algorithm for Blocking Artifacts Reduction

An algorithm for blocking artifacts reduction in DCT domain for block-based image coding was developed. The algorithm is based on the projection onto convex set （POCS） theory. Due to the fact that the DCT characteristics of shifted blocks are different caused by the blocking artifacts, a novel smoothness constraint set and the corresponding projection operator were proposed to reduce the blocking artifacts by discarding the undesired high frequency coefficients in the shifted DCT blocks. The experimental resuhs show that the propo,sed algorithm outperforms the conventional algorithms in terms of objective quality, subiective quality, and convergence property.

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.

An adaptive fuzzy filter for coding artifacts removal in video and image

This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based video coder. The proposed method concentrates on blocking and ringing artifacts removal. For de-blocking, the blocking strength is identified to determine the filtering range, and the maximum quantization parameter of the image is used to adapt the 1D fuzzy filter. For de-ringing, besides the edge detection, a complementary ringing detection method is proposed to locate the neglected ringing blocks, and the gradient threshold is adopted to adjust the parameter of 2D fuzzy filter. Experiments are performed on the MPEG-4 sequences. Compared with other methods, the proposed one achieves better detail preservation and artifacts removal performance with lower computational cost.

Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding(HEVC)frames and improves its subjective visual quality in multimedia services over communication networks.However,on faster processing of the complex videos at a low bitrate,some visible artifacts considerably degrade the picture quality.In this paper,we proposed a four-step fuzzy based adaptive deblocking filter selection technique.The proposed method removes the quantization noise,blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate.We have considered Y(luma),U(chromablue),and V(chroma-red)components parallelly.Finally,we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants,namely up 45◦,down 45◦,up 135◦,and down 135◦across horizontal and vertical block boundaries.In this context,experimentation is done on a wide variety of videos.An objective and subjective analysis is carried out with MATLAB software and Human Visual System(HVS).The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate.In the proposed method,we achieved 0.32–0.97 dB values of YPSNR.Our method achieved a BD_rate of+1.69%for the luma component,−0.18%(U)and−1.99%(V)for chroma components,respectively,with respect to the stateof-the-art methods.The proposed method proves to have low computational complexity and has better parallel processing,hence suitable for a real-time system in the near future.

Novel Efficient De-blocking Method for Highly Compressed Images

Due to coarse quantization, block-based discrete cosine transform(BDCT) compression methods usually suffer from visible blocking artifacts at the block boundaries. A novel efficient de-blocking method in DCT domain is proposed. A specific criterion for edge detection is given, one-dimensional DCT is applied on each row of the adjacent blocks and the shifted block in smooth region, and the transform coefficients of the shifted block are modified by weighting the average of three coefficients of the block. Mean square difference of slope criterion is used to judge the efficiency of the proposed algorithm. Simulation results show that the new method not only obtains satisfactory image quality, but also maintains high frequency information.

MAP based blocking artifact reduction for DCT domain distributed video coding

This paper proposes a maximum a posteriori （MAP） based blocking artifact reduction algorithm for discrete cosine transform （DCT） domain distributed video coding, in which the SI and the initial reconstructed Wyner-Ziv （WZ） frame are utilized to further estimate the original WZ frame. Though the MAP estimate improves quality of the artifact region, it also leads to over-smoothness and decreases quality of the non-artifact region. To overcome this problem, a criterion is presented to discriminate the artifact and the non-artifact region in the initial reconstructed WZ frame, and only the artifact region is updated with the MAP estimate. Simulation results show that the proposed algorithm provides obvious improvement in terms of both objective and subjective evaluations.

An adaptive preprocessing algorithm for low bitrate video coding

At low bitrate, all block discrete cosine transform (BDCT) based video coding algorithms suffer from visible blocking and ringing artifacts in the reconstructed images because the quantization is too coarse and high frequency DCT coefficients are inclined to be quantized to zeros. Preprocessing algorithms can enhance coding efficiency and thus reduce the likelihood of blocking artifacts and ringing artifacts generated in the video coding process by applying a low-pass filter before video encoding to remove some relatively insignificant high frequent components. In this paper, we introduce a new adaptive preprocessing algo- rithm, which employs an improved bilateral filter to provide adaptive edge-preserving low-pass filtering which is adjusted ac- cording to the quantization parameters. Whether at low or high bit rate, the preprocessing can provide proper filtering to make the video encoder more efficient and have better reconstructed image quality. Experimental results demonstrate that our proposed preprocessing algorithm can significantly improve both subjective and objective quality.

Quality assessment for JPEG images based on difference of power spectrum distribution

No-reference quality assessment aims at designing objective assessment criteria consistent to subjective perceived quality without any knowledge about reference image. This paper proposes a no-reference quality assessment algorithm specific to JPEG images. Blocking artifact in JPEG images is caused by the block based quantization of frequency coefficients, which is equivalent to applying low pass filtering in each block. In view of this idea, the algorithm in this paper was used to realize the quality assessment of JPEG images by quantizing the difference of power spectrum distribution between inner-block and inter-block. The assessment method proposed in this paper owns low algorithm complexity, clear physical meanings, free from learning and training and other advantages. Compared with most presented algorithms, the assessment results of proposed algorithm demonstrate a higher correlation to the subjective perceived quality.