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

Abstract

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.