Results 161 to 170 of about 15,429 (227)

A DNA Data Storage Method Using Spatial Encoding Based Lossless Compression. [PDF]

Entropy (Basel)
Şatır E.
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Achieving Robotic Data Efficiency Through Machine-Centric FDCT Vision Processing. [PDF]

Sensors (Basel)
Wiseman Y.
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Hybrid deep learning architecture for scalable and high-quality image compression. [PDF]

Sci Rep
Al-Khafaji M, Ramaha NTA.
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The Psyche Multispectral Imager Investigation: Characterizing the Geology, Topography, and Multispectral Properties of a Metal-Rich World. [PDF]

Space Sci Rev
Bell JF, Ravine MA, Caplinger MA, Schaffner JA, Brylow SM, Clark MJ, Peckham DA, Otjens PT, Price GJ, Rowell T, Ravine JW, Laramee JD, Juergens RC, Morgan W, Parker AG, Williams DA, Winhold A, Dibb S, Cisneros E, Walworth M, Zigo H, Auchterlonie L, Warner N, Bates-Tarasewicz H, Amiri N, Polanskey C, Mastrodemos N, Park RS, Alonge NK, Jaumann R, Binzel RP, McCoy TJ, Martin MG, Arthur PA.   +33 more
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Near lossless image compression system

2012 Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, 2012
Image compression has become an important issue in relation to storage and transmission. A very simple and efficient near lossless image compression system is suggested in this paper. In the forward compression algorithm, image pixels are shifted right by the base value.
A. S. Mamatha, Vipula Singh
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Near‐lossless compression methods for spectral images

Color Research & Application, 2011
AbstractIn this work, several near‐lossless compression methods for spectral images have been analyzed and compared. These methods are based both on the principal component analysis (PCA) and on the choice of a minimum number of spectral points, selected following different criteria.
CIPRIAN, Roberta, Carbucicchio, M.
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Near-Lossless Compression of Hyperspectral Images

2006 International Conference on Image Processing, 2006
Research Supported By National Science Foundation Grant Number Ccr-0104800. Richard Ladner was supported in part by the Boeing Professor-ship in Computer Science and Engineering. Contact Information: Professor Agnieszka Miguel, Department of Electrical & Computer Engineering Seattle University, 901 12th Avenue, P.O. Box 222000, Seattle, WA 98122-1090, (
Agnieszka Miguel, Jenny Liu, Dane Barney, Richard Ladner, Eve Riskin   +4 more
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Hypergraphs for Near-lossless Volumetric Compression

Fourth International Conference on Information Technology (ITNG'07), 2007
A hypergraphs-based image representation is already used for 2D lossless image compression. In this paper we extend this hypergraph representation on 3D-image and we add an alpha-tolerance. This extended representation conducts to a generalisation of the HLC lossless compression algorithm (A. Bretto and and L.
Luc Gillibert, Alain Bretto
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