%0 Conference Proceedings
%T Subspaces Clustering Approach to Lossy Image Compression
%+ Uniwersytet Jagielloński w Krakowie = Jagiellonian University (UJ)
%+ AGH University of Science and Technology [Krakow, PL] (AGH UST)
%A Spurek, Przemysław
%A Śmieja, Marek
%A Misztal, Krzysztof
%Z Part 8: Pattern Recognition and Image Processing
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Ho Chi Minh City, Vietnam
%Y Khalid Saeed
%Y Václav Snášel
%I Springer
%3 Computer Information Systems and Industrial Management
%V LNCS-8838
%P 571-579
%8 2014-11-05
%D 2014
%R 10.1007/978-3-662-45237-0_52
%K lossy compression
%K image compression
%K subspaces clustering
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X In this contribution lossy image compression based on subspaces clustering is considered. Given a PCA factorization of each cluster into subspaces and a maximal compression error, we show that the selection of those subspaces that provide the optimal lossy image compression is equivalent to the 0-1 Knapsack Problem. We present a theoretical and an experimental comparison between accurate and approximate algorithms for solving the 0-1 Knapsack problem in the case of lossy image compression.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01405649/document
%2 https://inria.hal.science/hal-01405649/file/978-3-662-45237-0_52_Chapter.pdf
%L hal-01405649
%U https://inria.hal.science/hal-01405649
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-LNCS-8838
%~ IFIP-CISIM