&lt;title&gt;Reconstruction artifacts in digital video compression&lt;/title&gt;

Yuen, Michael; Wu, Hong Ren

doi:10.1117/12.206383

Cited by 17 publications

(5 citation statements)

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“…From the various state-of-the-art algorithms, we choose two methods, which provide best results and represent two different approaches to artifact reduction. The first method is a combination of twomode deblocking [2] (which uses a grid position) and deringing filter proposed by A. Kaup [3]. The second algorithm is an efficient but very expensive technique of A. Nostratinia [4].…”

Section: Results Of Experimentsmentioning

confidence: 99%

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Coding Artifact Reduction using Non-Reference Block Grid Visibility Measure

Kirenko

Muijs

Shao

2006

2006 IEEE International Conference on Multimedia and Expo

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In this work a new method is proposed for coding artifact reduction of MPEG compressed video sequences. The method makes use of a simple cost-effective technique that allows the block grid position and its visibility to be determined without the need for access to the coding parameters. This information, combined with the results of local spatial analysis of luminance and chrominance components of a decoded image, is used to effectively suppress coding artifacts while preserving the sharpness of object edges. Results of our experiments confirm the high efficiency of the proposed approach.

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Section: Results Of Experimentsmentioning

confidence: 99%

“…Different techniques have been studied extensively in the past few years aimed at the reduction of blockiness and ringing in decoded sequences [2], [3], [4]. The state-of-theart methods are able to significantly reduce the visibility of coding artifacts.…”

Section: Introductionmentioning

confidence: 99%

Coding Artifact Reduction using Non-Reference Block Grid Visibility Measure

Kirenko

Muijs

Shao

2006

2006 IEEE International Conference on Multimedia and Expo

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“…One solution is to reduce the coding artifacts before applying resolution upscaling. However, most coding artifact reduction algorithms [8][9][10][11] blur details while suppressing various digital artifacts. Those details lost during artifact reduction cannot be recovered during resolution upscaling.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Resolution Upconversion for Compressed Video Using Pixel Classification

Shao

2007

EURASIP J. Adv. Signal Process.

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A novel adaptive resolution upconversion algorithm that is robust to compression artifacts is proposed. This method is based on classification of local image patterns using both structure information and activity measure to explicitly distinguish pixels into content or coding artifacts. The structure information is represented by adaptive dynamic-range coding and the activity measure is the combination of local entropy and dynamic range. For each pattern class, the weighting coefficients of upscaling are optimized by a least-mean-square (LMS) training technique, which trains on the combination of the original images and the compressed downsampled versions of the original images. Experimental results show that our proposed upconversion approach outperforms other classification-based upconversion and artifact reduction techniques in concatenation.

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“…A large number of coding artifact reduction algorithms have been developed [2] to improve the perceived picture quality. Often, such algorithms include processing steps to distinguish artifacts from video data, to measure and/or estimate the visibility of the artifacts, and to reduce the artifacts by means of filtering.…”

Section: Coding Artifactsmentioning

confidence: 99%