Progressive Lossy-to-Lossless Compression of DNA Microarray Images

Persistent Link:
http://hdl.handle.net/10150/615540
Title:
Progressive Lossy-to-Lossless Compression of DNA Microarray Images
Author:
Hernandez-Cabronero, Miguel; Blanes, Ian; Pinho, Armando J.; Marcellin, Michael W.; Serra-Sagrista, Joan
Affiliation:
Univ Arizona, Dept Elect & Comp Engn
Issue Date:
2016-05
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation:
Progressive Lossy-to-Lossless Compression of DNA Microarray Images 2016, 23 (5):698 IEEE Signal Processing Letters
Journal:
IEEE Signal Processing Letters
Rights:
© 2016 IEEE.
Collection Information:
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
Abstract:
The analysis techniques applied to DNA microarray images are under active development. As new techniques become available, it will be useful to apply them to existing microarray images to obtain more accurate results. The compression of these images can be a useful tool to alleviate the costs associated to their storage and transmission. The recently proposed Relative Quantizer (RQ) coder provides the most competitive lossy compression ratios while introducing only acceptable changes in the images. However, images compressed with the RQ coder can only be reconstructed with a limited quality, determined before compression. In this work, a progressive lossy-to-lossless scheme is presented to solve this problem. First, the regular structure of the RQ intervals is exploited to define a lossy-to-lossless coding algorithm called the Progressive RQ (PRQ) coder. Second, an enhanced version that prioritizes a region of interest, called the PRQ-region of interest (ROI) coder, is described. Experiments indicate that the PRQ coder offers progressivity with lossless and lossy coding performance almost identical to the best techniques in the literature, none of which is progressive. In turn, the PRQ-ROI exhibits very similar lossless coding results with better rate-distortion performance than both the RQ and PRQ coders.
ISSN:
1070-9908; 1558-2361
DOI:
10.1109/LSP.2016.2547893
Keywords:
DNA microarray images; image compression; quantization
Version:
Final accepted manuscript
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7442802

Full metadata record

DC FieldValue Language
dc.contributor.authorHernandez-Cabronero, Miguelen
dc.contributor.authorBlanes, Ianen
dc.contributor.authorPinho, Armando J.en
dc.contributor.authorMarcellin, Michael W.en
dc.contributor.authorSerra-Sagrista, Joanen
dc.date.accessioned2016-07-05T19:53:44Z-
dc.date.available2016-07-05T19:53:44Z-
dc.date.issued2016-05-
dc.identifier.citationProgressive Lossy-to-Lossless Compression of DNA Microarray Images 2016, 23 (5):698 IEEE Signal Processing Lettersen
dc.identifier.issn1070-9908-
dc.identifier.issn1558-2361-
dc.identifier.doi10.1109/LSP.2016.2547893-
dc.identifier.urihttp://hdl.handle.net/10150/615540-
dc.description.abstractThe analysis techniques applied to DNA microarray images are under active development. As new techniques become available, it will be useful to apply them to existing microarray images to obtain more accurate results. The compression of these images can be a useful tool to alleviate the costs associated to their storage and transmission. The recently proposed Relative Quantizer (RQ) coder provides the most competitive lossy compression ratios while introducing only acceptable changes in the images. However, images compressed with the RQ coder can only be reconstructed with a limited quality, determined before compression. In this work, a progressive lossy-to-lossless scheme is presented to solve this problem. First, the regular structure of the RQ intervals is exploited to define a lossy-to-lossless coding algorithm called the Progressive RQ (PRQ) coder. Second, an enhanced version that prioritizes a region of interest, called the PRQ-region of interest (ROI) coder, is described. Experiments indicate that the PRQ coder offers progressivity with lossless and lossy coding performance almost identical to the best techniques in the literature, none of which is progressive. In turn, the PRQ-ROI exhibits very similar lossless coding results with better rate-distortion performance than both the RQ and PRQ coders.en
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7442802en
dc.rights© 2016 IEEE.en
dc.subjectDNA microarray imagesen
dc.subjectimage compressionen
dc.subjectquantizationen
dc.titleProgressive Lossy-to-Lossless Compression of DNA Microarray Imagesen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Elect & Comp Engnen
dc.identifier.journalIEEE Signal Processing Lettersen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal accepted manuscripten
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