Title :
Lossy compression of hyperspectral images using online learning based sparse coding
Author :
Ulku, Irem ; Toreyin, B. Ugur
Author_Institution :
Dept. of Electr. & Electron. Eng., Cankaya Univ., Ankara, Turkey
Abstract :
A lossy hyperspectral image compression method is proposed using online learning based sparse coding. The least number of coefficients are obtained to represent hyperspectral images by applying the sparse coding algorithm which is based on a dicriminative online dictionary learning method. Results indicate that a pre-analysis of the number of non-zero dictionary elements may help in improving the overall compression quality.
Keywords :
compressed sensing; data compression; hyperspectral imaging; image coding; dicriminative online dictionary learning method; lossy hyperspectral image compression method; sparse coding algorithm; Dictionaries; Encoding; Equations; Hyperspectral imaging; Image coding; Mathematical model; PSNR; Anomaly Detection; Hyperspectral Imagery; Online Learning; Sparse Coding;
Conference_Titel :
Computational Intelligence for Multimedia Understanding (IWCIM), 2014 International Workshop on
Conference_Location :
Paris
DOI :
10.1109/IWCIM.2014.7008809
