Logarithmical hopping encoding: a low computational complexity algorithm for image compression

Garcia Aranda, Jose María and González Casquete, Marina and Cao Cueto, Mario and Navarro Salmerón, Joaquín and González Vidal, Francisco (2015). Logarithmical hopping encoding: a low computational complexity algorithm for image compression. "IET Image Processing", v. 9 (n. 8); pp. 643-651. ISSN 1751-9659. https://doi.org/10.1049/iet-ipr.2014.0421.

Description

Title: Logarithmical hopping encoding: a low computational complexity algorithm for image compression
Author/s:
  • Garcia Aranda, Jose María
  • González Casquete, Marina
  • Cao Cueto, Mario
  • Navarro Salmerón, Joaquín
  • González Vidal, Francisco
Item Type: Article
Título de Revista/Publicación: IET Image Processing
Date: August 2015
ISSN: 1751-9659
Volume: 9
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

LHE (logarithmical hopping encoding) is a computationally efficient image compression algorithm that exploits the Weber–Fechner law to encode the error between colour component predictions and the actual value of such components. More concretely, for each pixel, luminance and chrominance predictions are calculated as a function of the surrounding pixels and then the error between the predictions and the actual values are logarithmically quantised. The main advantage of LHE is that although it is capable of achieving a low-bit rate encoding with high quality results in terms of peak signal-to-noise ratio (PSNR) and image quality metrics with full-reference (FSIM) and non-reference (blind/referenceless image spatial quality evaluator), its time complexity is O( n) and its memory complexity is O(1). Furthermore, an enhanced version of the algorithm is proposed, where the output codes provided by the logarithmical quantiser are used in a pre-processing stage to estimate the perceptual relevance of the image blocks. This allows the algorithm to downsample the blocks with low perceptual relevance, thus improving the compression rate. The performance of LHE is especially remarkable when the bit per pixel rate is low, showing much better quality, in terms of PSNR and FSIM, than JPEG and slightly lower quality than JPEG-2000 but being more computationally efficient.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainIPT-2011-1683-430000INNPACTOUnspecifiedUnspecified

More information

Item ID: 37459
DC Identifier: http://oa.upm.es/37459/
OAI Identifier: oai:oa.upm.es:37459
DOI: 10.1049/iet-ipr.2014.0421
Official URL: http://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2014.0421
Deposited by: Memoria Investigacion
Deposited on: 15 Sep 2015 16:15
Last Modified: 31 May 2019 17:39
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