Title :
Compression of microarray images using a binary tree decomposition
Author :
Matos, Luis M. O. ; Neves, Antonio J. R. ; Pinho, Armando J.
Author_Institution :
DETI, Univ. of Aveiro, Aveiro, Portugal
Abstract :
This paper proposes a lossless compression method for microarray images, based on a hierarchical organization of the intensity levels followed by finite-context modeling. A similar approach was recently applied to medical images with success. The goal of this work was to further extend, adapt and evaluate this approach to the special case of microarray images. We performed simulations on seven different data sets (total of 254 images). On average, the proposed method attained ~ 9% better results when compared to the best compression standard (JPEG-LS).
Keywords :
data compression; image coding; lab-on-a-chip; medical image processing; trees (mathematics); DNA microarray imaging; JPEG-LS; binary tree decomposition; finite-context modeling; hierarchical organization; intensity levels; lossless compression method; medical images; microarray images; Binary trees; Codecs; Context; Decoding; Image coding; Standards organizations; Binary tree decomposition; lossless compression; microarray images;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon