A Novel Video Coding Framework with Tensor Representation for Efficient Video Streaming

Athisayamani, Suganya; Dejey,

doi:10.1007/s11277-019-06704-4

Cited by 2 publications

(3 citation statements)

References 29 publications

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“…In this paper, a synthesis analysis based video compression method is proposed using tensor as a representation to store the intermediate data such as segments of different types. The tensor representation reduces the amount of side information and useful in video compression [14], [15].…”

Section: Fig1 Video Codec Using Synthesis Analysismentioning

confidence: 99%

“…The decomposition is shown in Eq. (15). (15) is the factor matrix that corresponds to the decomposed signal of the input segments in temporal axis.…”

Section: Dynamic Texture Fusionmentioning

confidence: 99%

“…(15). (15) is the factor matrix that corresponds to the decomposed signal of the input segments in temporal axis. In the proposed method, the value of t is five that represents the B-frame count in the video coding scheme.…”

Section: Dynamic Texture Fusionmentioning

confidence: 99%

See 2 more Smart Citations

Synthesis Analysis Methods for Underwater Video Compression with Tensor Based Minimized Side Information

Singh¹,

Suganya²

2019

IJEAT

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Synthesis analysis is a common approach used to compress videos with more amounts of dynamic textures. Underwater videos contain more moving species captured by moving camera. These kinds of videos have two types of motion registered by both the species and the camera. In this paper, tensor, an N-way representation of data is used to store the side information obtained from the synthesis analysis approach. The Low multilinear rank approximation (LMLRA) with error correction using residual tensor is applied on the side information to reduce the memory space for side information. The host encoder in synthesis analysis approach plays an important role in providing high compression rate with minimal loss and hence H.265 is used as the host encoder. The results show that the proposed method achieves highest compression ratio with minimal loss due to distortion and saved bit rate which is highly consumed by dynamic textures.

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Section: Fig1 Video Codec Using Synthesis Analysismentioning

confidence: 99%

“…The decomposition is shown in Eq. (15). (15) is the factor matrix that corresponds to the decomposed signal of the input segments in temporal axis.…”

Section: Dynamic Texture Fusionmentioning

confidence: 99%