Median Predictor-based Lossless Video Compression Algorithm for IR Image Sequences

Lossless image compression has long been recognised as an important need for several applications such as medical imaging, storage of critical IR image sequences, and remote sensing. In this paper, a simple, fast and easy to realisable-on-hardware lossless video compression algorithm is proposed that is well-suited for IR imageries. Context-based median predictor is used for prediction of reference pixels. Three neighboring pixels are used as context for prediction. Inter-frame coding is performed by encoding the redundant pixels in an efficient way, using 1-bit code. Finally, the arithmetic coder is used as entropy coding. The proposed algorithm is able to operate in image compression and video compression mode. The proposed Median Predictor based Lossless Video Compression (MPLVC) algorithm is compared with Joint Pictures Experts Group-Lossless (JPEG-LS) and Fast and Efficient Lossless Image Compression System (FELICS) for compression performance. The results demonstrate that proposed algorithm is superior in encoding rate with added advantage in simplicity and ease in realization on hardware.Defence Science Journal, 2009, 59(2), pp.183-188, DOI:http://dx.doi.org/10.14429/dsj.59.150

Visually lossless compression of digital hologram sequences

Digital hologram sequences have great potential for the recording of 3D scenes of moving macroscopic objects as their numerical reconstruction can yield a range of perspective views of the scene. Digital holograms inherently have large information content and lossless coding of holographic data is rather inefficient due to the speckled nature of the interference fringes they contain. Lossy coding of still holograms and hologram sequences has shown promising results. By definition, lossy compression introduces errors in the reconstruction. In all of the previous studies, numerical metrics were used to measure the compression error and through it, the coding quality. Digital hologram reconstructions are highly speckled and the speckle pattern is very sensitive to data changes. Hence, numerical quality metrics can be misleading. For example, for low compression ratios, a numerically significant coding error can have visually negligible effects. Yet, in several cases, it is of high interest to know how much lossy compression can be achieved, while maintaining the reconstruction quality at visually lossless levels. Using an experimental threshold estimation method, the staircase algorithm, we determined the highest compression ratio that was not perceptible to human observers for objects compressed with Dirac and MPEG- 4 compression methods. This level of compression can be regarded as the point below which compression is perceptually lossless although physically the compression is lossy. It was found that up to 4 to 7.5 fold compression can be obtained with the above methods without any perceptible change in the appearance of video sequences

Lossless Intra Coding in HEVC with 3-tap Filters

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for prediction, based on the angular projection idea borrowed from block-based intra prediction in lossy coding. This paper explores a method which uses three neighboring pixels for prediction according to a two-dimensional correlation model, and the used neighbor pixels and prediction weights change depending on intra mode. To find the best prediction weights for each intra mode, a two-stage offline optimization algorithm is used and a number of implementation aspects are discussed to simplify the proposed prediction method. The proposed method is implemented in the HEVC reference software and experimental results show that the explored 3-tap filtering method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC. The proposed method also decreases average decoding time by 12.7% while it increases average encoding time by 9.7%Comment: 10 pages, 7 figure

Adaptive temporal decimation algorithm with dynamic time window

Published versio

JND-Based Perceptual Video Coding for 4:4:4 Screen Content Data in HEVC

The JCT-VC standardized Screen Content Coding (SCC) extension in the HEVC HM RExt + SCM reference codec offers an impressive coding efficiency performance when compared with HM RExt alone; however, it is not significantly perceptually optimized. For instance, it does not include advanced HVS-based perceptual coding methods, such as JND-based spatiotemporal masking schemes. In this paper, we propose a novel JND-based perceptual video coding technique for HM RExt + SCM. The proposed method is designed to further improve the compression performance of HM RExt + SCM when applied to YCbCr 4:4:4 SC video data. In the proposed technique, luminance masking and chrominance masking are exploited to perceptually adjust the Quantization Step Size (QStep) at the Coding Block (CB) level. Compared with HM RExt 16.10 + SCM 8.0, the proposed method considerably reduces bitrates (Kbps), with a maximum reduction of 48.3%. In addition to this, the subjective evaluations reveal that SC-PAQ achieves visually lossless coding at very low bitrates.Comment: Preprint: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018