20 papers · ranked by Valyu relevance
Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu + 6 more
With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high-efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two-stage framework with high computational complexity and frequently struggle to…
Huan Deng, Dan Song, Zhiping Xu, Yanglong Sun + 2 more
'Bal S. Virdee'] In the Internet of Things, sensor nodes collect environmental information and utilize lossy compression for saving storage space. To achieve this objective, high-efficiency compression of the continuous source should be studied. Different from existing schemes, lossy source coding is implemented based…
Albert No
We established a universality of logarithmic loss over a finite alphabet as a distortion criterion in fixed-length lossy compression. For any fixed-length lossy-compression problem under an arbitrary distortion criterion, we show that there is an equivalent lossy-compression problem under logarithmic loss. The…
Shubham Chandak, Kedar Tatwawadi, Srivatsan Sridhar, Tsachy Weissman
Nanopore sequencing provides a real-time and portable solution to genomic sequencing, with long reads enabling better assembly and structural variant discovery than second generation technologies. The nanopore sequencing process generates huge amounts of data in the form of raw current data, which must be compressed to…
Yibo Yang, Stephan Mandt, Lucas Theis
Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new possibilities for data compression, allowing compression algorithms to be learned end-to-end from data using powerful generative models such…
Jerry Gibson
Shannon introduced the fields of information theory and rate distortion theory in his landmark 1948 paper [1], where he defined “The Rate for a Source Relative to a Fidelity Evaluation.” Shannon officially coined the term “rate distortion function” in his seminal contribution in 1959 [2]. The 1950s, 1960s and 1970s…
Sukhpal Singh
In JPEG (DCT based) compresses image data by representing the original image with a small number of transform coefficients. It exploits the fact that for typical images a large amount of signal energy is concentrated in a small number of coefficients. The goal of DCT transform coding is to minimize the number of…
Rogshan Yu, Wenxian Yang
Per-base quality values in NGS sequencing data take a significant portion of storage even after compression. Lossy compression technologies could further reduce the space used by quality values. However, in many applications lossless compression is still desired. Hence, sequencing data in multiple file formats have to…
Hendrik Vincent Koops, Gianluca Micchi, Elio Quinton
Previous research contributions on blind lossy compression identification report near perfect performance metrics on their test set, across a variety of codecs and bit rates. However, we show that such results can be deceptive and may not accurately represent true ability of the system to tackle the task at hand. In…
A. M. Raid, Wael M. Khedr, M. A. El-Dosuky, Wesam Ahmed
Due to the increasing requirements for transmission of images in computer, mobile environments, the research in the field of image compression has increased significantly. Image compression plays a crucial role in digital image processing, it is also very important for efficient transmission and storage of images. When…
Tiantian Li, Qunbing Xia, Yue Li, Ruixiao Guo + 1 more
Learning-based lossless image compression employs pixel-based or subimage-based auto-regression for probability estimation, which achieves desirable performances. However, the existing works only consider context dependencies in one direction, namely, those symbols that appear before the current symbol in raster order.…
Nithin Nagaraj, Arun Somani
Error detection is a fundamental need in most computer networks and communication systems in order to combat the effect of noise. Error detection techniques have also been incorporated with lossless data compression algorithms for transmission across communication networks. In this paper, we propose to incorporate a…
Simon Wiedemann, Heiner Kirchoffer, Stefan Matlage, Paul T. Haase + 9 more
'Arturo Marbán' 'Talmaj Marinč' 'David L. Neumann' 'Tung Thanh Nguyen' 'Ahmed Osman' 'Detlev Marpe' 'Heiko Schwarz' 'Thomas Wiegand' 'Wojciech Samek'] Abstract—The field of video compression has developed some of the most sophisticated and efficient compression algorithms known in the literature, enabling very high…
Tomasz Grajek, Jakub Stankowski, Damian Karwowski, Krzysztof Klimaszewski + 2 more
'Krzysztof Klimaszewski' 'Olgierd Stankiewicz' 'Krzysztof Wegner'] Abstract—The paper presents quantitative analysis of the video quality losses in the homogenous HEVC video transcoder. With the use of HM15.0 reference software and a set of test video sequences, cascaded pixel domain video transcoder (CPDT) concept has…
Grzegorz Ulacha, Ryszard Stasiński, Cezary Wernik
In this paper, the most efficient (from data compaction point of view) and current image lossless coding method is presented. Being computationally complex, the algorithm is still more time efficient than its main competitors. The presented cascaded method is based on the Weighted Least Square (WLS) technique, with…
Claudio Albert, Tom Paridaens, Jan Voges, Daniel Naro + 9 more
The MPEG-G standardization initiative is a coordinated international effort to specify a compressed data format that enables large scale genomic data to be processed, transported and shared. The standard consists of a set of specifications (i.e., a book) describing: i) a nor-mative format syntax, and ii) a normative…
Vida Ravanmehr, Minji Kim, Zhiying Wang, Olgica Milenković
The past decade has witnessed a rapid development of data acquisition technologies that enable integrative genomic and proteomic analysis. One such technology is chromatin immunoprecipitation sequencing (ChIP-seq), developed for analyzing interactions between proteins and DNA via next-generation sequencing…
Anas Al-okaily, Abdelghani Tbakhi
Data compression is a challenging and increasingly important problem. As the amount of data generated daily continues to increase, efficient transmission and storage has never been more critical. In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated…
Chen-Hsiu Huang, Ja-Ling Wu, Jun Chen
End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational…
Paweł Pawłowski, Karol Piniarski, Adam Dąbrowski
In this paper we present a highly efficient coding procedure, specially designed and dedicated to operate with high dynamic range (HDR) RCCC (red, clear, clear, clear) image sensors used mainly in advanced driver-assistance systems (ADAS) and autonomous driving systems (ADS). The coding procedure can be used for a…