19 papers · ranked by Valyu relevance
Amir Said
Entropy coding, compression, complexity This introduction to arithmetic coding is divided in two parts. The first explains how and why arithmetic coding works. We start presenting it in very general terms, so that its simplicity is not lost under layers of implementation details. Next, we show some of its basic…
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…
Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul T. Haase + 8 more
'Arturo Marbán' 'Talmaj Marinč' 'David L. Neumann' 'Ahmed Osman' 'Detlev Marpe' 'Heiko Schwarz' 'Thomas Wiegand' 'Wojciech Samek'] We present DeepCABAC, a novel contextadaptive binary arithmetic coder for compressing deep neural networks. It quantizes each weight parameter by minimizing a weighted rate-distortion…
Jingjian Li, Wei Wang, Hong Mo, Mengting Zhao + 3 more
'Derya Malak' 'Song-Nam Hong'] A distributed arithmetic coding algorithm based on source symbol purging and using the context model is proposed to solve the asymmetric Slepian-Wolf problem. The proposed scheme is to make better use of both the correlation between adjacent symbols in the source sequence and the…
Junwei Zhou, HaoYun Xiao, Jianwen Xi, Qiuzhen Lin
—Distributed Arithmetic Coding (DAC) has emerged as a feasible solution to the Slepian-Wolf problem, particularly in scenarios with non-stationary sources and for data sequences with lengths ranging from small to medium. Due to the inherent decoding ambiguity in DAC, the number of candidate paths grows exponentially…
Tilo Strutz, Roman Rischke
—The transmission or storage of signals typically involves data compression. The final processing step in compression systems is generally an entropy coding stage, which converts symbols into a bit stream based on their probability distribution. A distinct class of entropy coding methods operates not by mapping input…
Wei-Gang Chen, Xun Wang
High efficiency video coding (HEVC) seeks the best code tree configuration, the best prediction unit division and the prediction mode, by evaluating the rate-distortion functional in a recursive way and using a “try all and select the best” strategy. Further, HEVC only supports context adaptive binary arithmetic coding…
Grzegorz Ulacha, Mirosław Łazoryszczak, T. Aaron Gulliver, Jun Chen
This paper presents a method for lossless compression of images with fast decoding time and the option to select encoder parameters for individual image characteristics to increase compression efficiency. The data modeling stage was based on linear and nonlinear prediction, which was complemented by a simple block for…
Tilo Strutz, Nico Schreiber
—There is a class of entropy-coding methods which do not substitute symbols by code words (such as Huffman coding), but operate on intervals or ranges. This class includes three prominent members: conventional arithmetic coding, range coding, and coding based on asymmetric numeral systems. To determine the correct…
Grzegorz Ulacha, Mirosław Łazoryszczak, Jun Chen, Sadaf Salehkalaibar
'Sadaf Salehkalaibar'] This paper presents a lossless image compression method with a fast decoding time and flexible adjustment of coder parameters affecting its implementation complexity. A comparison of several approaches for computing non-MMSE prediction coefficients with different levels of complexity was made.…
Hsi-Chin Hsin, Tze-Yun Sung, Yaw-Shih Shieh
High-efficiency, high-quality biomedical image compression is desirable especially for the telemedicine applications. This paper presents an adaptive coding pass scanning (ACPS) algorithm for optimal rate control. It can identify the significant portions of an image and discard insignificant ones as early as possible.…
Winfield Chen, Lloyd T. Elliott
We improve the efficiency of population genetic file formats and GWAS computation by leveraging the distribution of sample ordering in population-level genetic data. We identify conditional exchangeability of these data, recommending finite state entropy algorithms as an arithmetic code naturally suited to population…
Ming Lu, Zhan Ma
—Questing for learned lossy image coding (LIC) with superior compression performance and computation throughput is challenging. The vital factor behind it is how to intelligently explore Adaptive Neighborhood Information Aggregation (ANIA) in transform and entropy coding modules. To this end, Integrated Convolution and…
Zhenghao Chen, Luping Zhou, Zhihao Hu, Dong Xu
Video Compression Authors: ['Zhenghao Chen' 'Luping Zhou' 'Zhihao Hu' 'Dong Xu'] Content-adaptive compression is crucial for enhancing the adaptability of the pre-trained neural codec for various contents. Although these methods have been very practical in neural image compression (NIC), their application in neural…
Vojtech Macala, Petr Simecek
Lossless compression and probabilistic sequence modeling are two faces of the same coin: a model that assigns high probability to a sequence can encode it in few bits via arithmetic coding. We exploit this duality to evaluate genomic language models as compressors of DNA, using compression primarily as an objective…
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…
Wiktor Młynarski, Ann M. Hermundstad
The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we develop a theoretical framework that can account for the dynamics of adaptation from an information-processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes…
Victor Geadah, Stefan Horoi, Giancarlo Kerg, Guy Wolf + 1 more
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still unclear how brain circuits exploit single-neuron flexibility, and how…
Authors not listed
For applications in gas sensing, purification, and capture, we often wish to search a large set of metal-organic frameworks (MOFs) for the top-K in terms of their Henry coefficient of an adsorbate. A molecular simulation to predict the Henry coefficient of a MOF constitutes a Monte Carlo integration where each sample…