DocumentCode :
2425915
Title :
Lossless Compression of Digital Mammography Using Fixed Block Segmentation and Pixel Grouping
Author :
Kumar, M. S Ravi ; Koliwad, Shivaprakash ; Dwarakish, G.S.
Author_Institution :
Dept. of lS&E., KVGCE, Sullia
fYear :
2008
fDate :
16-19 Dec. 2008
Firstpage :
201
Lastpage :
206
Abstract :
A mammography is a specific type of imaging that uses low-dose x-ray system to examine breasts. This is an efficient means of early detection of breast cancer. High resolution is a common characteristic of such images. Archiving and retaining these data for at least three years is expensive, difficult and requires sophisticated data compression techniques. In this paper an efficient method is proposed for lossless compression of mammography images. After performing de-correlation of the image using two efficient predictors, the residue image is divided into 4times4 blocks. The blocks with all-zero pixels are identified using one bit code. Later, Second order of pixel grouping is employed to the remaining blocks to increase the coding efficiency. Such blocks are coded using Base offset method. Special techniques are used to save the header information. The method is tested using 25 mammograms from the MIAS database, each having a resolution of 1024times1024 pixels with 8 bits/pixel. Experimental results indicate better compression ratio when compared to JPEG 2000, JPEG-LS, PNG and JBIG.
Keywords :
cancer; data compression; image coding; image resolution; image segmentation; mammography; medical image processing; Base offset method; JBIG; JPEG 2000; JPEG-LS; MIAS database; PNG; breast cancer detection; data compression techniques; digital mammography; fixed block segmentation; lossless compression; low-dose x-ray system; mammography images; pixel grouping; Breast cancer; Cancer detection; Data compression; High-resolution imaging; Image coding; Image resolution; Image segmentation; Mammography; Optical imaging; X-ray imaging; JPEG 2000; JPEG-LS; Lossless compression; mammography image compression; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, Graphics & Image Processing, 2008. ICVGIP '08. Sixth Indian Conference on
Conference_Location :
Bhubaneswar
Print_ISBN :
978-0-7695-3476-3
Electronic_ISBN :
978-0-7695-3476-3
Type :
conf
DOI :
10.1109/ICVGIP.2008.54
Filename :
4756071
Link To Document :
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