Lossless compression of video using temporal information

Abstract

In this paper, we consider the problem of lossless compression of video by taking into account temporal information. Video lossless compression is an interesting possibility in the line of production and contribution. We propose a compression technique which is based on motion compensation, optimal three-dimensional (3-D) linear prediction and context based Golomb-Rice entropy coding. The proposed technique is compared with 3-D extensions of the JPEG-LS standard for still image compression. A compression gain of about 0.8 bit/pel with respect to static JPEG-LS, applied on a frame-by-frame basis, is achievable at a reasonable computational complexity.

Lossless video compression based on backward adaptive pixel-based fast motion estimation

“…The uncompressed side information requires 2log 2 (2 × search range)/(block size) 2 bpp. We compress it with the state-of-the-art JPEG-LS as in [8], the overall entropy including compressed side information is shown in parentheses. In our experiment BAPME is superior to conventional block-based FS in terms of overall zero-order entropy by a significant margin.…”

“…BMA is simple and efficient. A large number of researchers employed and improved BMA in their lossless video compression schemes [7,8,9,10,11]. Memon and Sayood were among the pioneers looking into the problem of lossless compression of video [7].…”

“…They presented a hybrid compression scheme that adaptively switches between the temporal predictor based on BMA and the spectral predictor which takes the best predictor among spectral planes. Brunello et al [8] introduced a temporal prediction scheme based on motion estimation and optimal 3-D linear prediction. Carotti et al [11] combined the CALIC [12] framework with a temporal predictor which uses multi-frame motion estimation and least square method to weigh predicted values from multiple frames.…”

“…While full search and fast search have been widely used in block-matching motion estimation [13,8], only full search is adopted by pixel-based schemes [16]. Fig.…”

Backward Adaptive Pixel-based Fast Predictive Motion Estimation

“…The uncompressed side information requires bits per pixel. If the side information is compressed, e.g., with JPEG-LS as in [2], the amount of bits required is shown in Table III. In our experiment BAPME is superior to conventional block-based FS algorithm in terms of overall zero-order entropy.…”