Compression at a very low bit rate(≤0.5bpp) causes degradation in video frames with standard decoding algorithms like H.261, H.262, H.264, and MPEG-1 and MPEG-4, which itself produces lots of artifacts. This paper focuses on an efficient pre-and post-processing technique (PP-AFT) to address and rectify the problems of quantization error, ringing, blocking artifact, and flickering effect, which significantly degrade the visual quality of video frames. The PP-AFT method differentiates the blocked images or frames using activity function into different regions and developed adaptive filters as per the classified region. The designed process also introduces an adaptive flicker extraction and removal method and a 2-D filter to remove ringing effects in edge regions. The PP-AFT technique is implemented on various videos, and results are compared with different existing techniques using performance metrics like PSNR-B, MSSIM, and GBIM. Simulation results show significant improvement in the subjective quality of different video frames. The proposed method outperforms state-of-the-art de-blocking methods in terms of PSNR-B with average value lying between (0.7–1.9db) while (35.83–47.7%) reduced average GBIM keeping MSSIM values very close to the original sequence statistically 0.978.

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.

The reconstructed images from JPEG compression produce noticeable image degradation near the block boundaries, in case of highly compressed images, because each block is transformed and quantized independently. The blocking effects are classified into three types of noises: staircase noise, grid noise and corner outlier out of which major thrust is laid on corner outlier in this paper. A post-processing algorithm is proposed to reduce the blocking artifacts of JPEG decompressed images. The proposed postprocessing algorithm, which consists of three stages, reduces the blocking artifacts efficiently. A comparative study between the proposed algorithm and other post-processing algorithms based on various performance indices is made. General TermsJPEG Compression, Corner outlier et.al.

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Block based Discrete Cosine Transform (BDCT) is commonly used to detect and remove blocking artifacts in the compressed images. We proposed spatial domain post processing algorithm with four fold model. In the initial stage, pixel vector (PV) is calculated for horizontal as well as vertical block boundaries, after defining PV calculation of different threshold values is made for extracting blocking artifacts. These thresholds are basically adaptive to the image quality due to strong correlation with the PV. To avoid ringing artifacts across block edges directional filter is proposed. Our research further worked on region classification based upon activity of PV within the blocks. Based upon different PV activity regions separate filters are used to achieve best filtering and finally Symmetrical Pixel Normalization filter (SPN Filter) is used to normalize the values of symmetrical pixel value for better visual performance . Proposed technique various indices like PSNR, MSSIM, GBIM are calculated and compare with different post processing techniques used in literature