Lossless Compression and Secured Video Transmission for Multi Cloud Storage Data

Abstract

In the multi cloud storage of data such as video, secure content protectionism an important achievement in emerging network architectures to address the exponential development of video transmission. This paper will perform a methodical improvement of ‘visually lossless’ (VL) threshold selection for Advanced Video Coding technique with video compression for the lossless transmission with entire content and motion of the video.  We consider a video streaming that will be converted to number of frames by 27 to 30 frames per second dependent based on quality of the video signal.  Input signal has to be encrypted for security purpose before transmission.  After encryption the video content have more memory space occupying nature, we have to apply the video compression technique for secured cloud communication through the wireless sensor networks (WSN).The distributed encoding source technique is used to secure the video frames without the data to be compressed prior to encryption.  The compression technique is used to decrease the dimension of the video after encrypting the video for transmission in secured manner. In the proposed work, we formulate a high efficiency video encryption-then-compression (ETC) technique for secured video transmission through the wireless sensor networks.  We are performing lossless video compression without losing data from the video to be transmitted even after encryption.  The proposed video encryption system is developed in the prediction error domain will be shown to be able to give high level security by applying encryption.  We will use Huffman coding technique for the compression of the video to make the video compression without bit error rate during the transmission.  The two dimensional transformation such as Discrete Wavelet Transform (2D DWT) could be applied to transform video as of spatial domain to domain of frequency to relate coding theorem such as Set Partition in Hierarchical Tree (SPIHT) methodology.  SPIHT along with technique of coding of video compression is applied for achieving high compression ratio lossless video compression.  The various parameters like PSNR, MSE, bits per pixel, compression ratio are estimated to prove the proposed system efficiency and accurate are high.