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Attaining a Super Quality Video from Multiple Compressed Copies Using IVEM


Affiliations
1 Karunya University, Coimbatore, Tamil Nadu, India
2 Department of Computer Science and Engineering, Karunya University, Coimbatore, Tamil Nadu, India
     

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A large number of communication application contains videos. Videos in compressed format are uploaded online and may have blocking artifacts and other clarity issues not pleasing to the human eye. This algorithm called Iterative Video Enhancement Method (IVEM) takes as input the several number of compressed copies that are available and gives as output a single video that is enhanced both objectively and subjectively without any artifacts. This algorithm makes use of two sets namely Smoothness Constraint Set for removing blocking artifacts and Quantization Constraint Set which is the set of all quantization coefficients. The video that is obtained as the output is superior in quality compared to the two compressed input copies. However, it is not of the same quality of the original source video. Hence the quality of the reconstructed video can be further enhanced by using super resolution – a technique used for up scaling video by using multiple frames of the same object to achieve a higher resolution video.

Keywords

Compression, Blocking Artifacts, Reconstruction, Super Resolution.
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  • Attaining a Super Quality Video from Multiple Compressed Copies Using IVEM

Abstract Views: 257  |  PDF Views: 3

Authors

Ann Mary Mathew
Karunya University, Coimbatore, Tamil Nadu, India
J. Anitha
Department of Computer Science and Engineering, Karunya University, Coimbatore, Tamil Nadu, India

Abstract


A large number of communication application contains videos. Videos in compressed format are uploaded online and may have blocking artifacts and other clarity issues not pleasing to the human eye. This algorithm called Iterative Video Enhancement Method (IVEM) takes as input the several number of compressed copies that are available and gives as output a single video that is enhanced both objectively and subjectively without any artifacts. This algorithm makes use of two sets namely Smoothness Constraint Set for removing blocking artifacts and Quantization Constraint Set which is the set of all quantization coefficients. The video that is obtained as the output is superior in quality compared to the two compressed input copies. However, it is not of the same quality of the original source video. Hence the quality of the reconstructed video can be further enhanced by using super resolution – a technique used for up scaling video by using multiple frames of the same object to achieve a higher resolution video.

Keywords


Compression, Blocking Artifacts, Reconstruction, Super Resolution.