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Author Karimi, N. ♦ Samavi, S. ♦ Shirani, S. ♦ Amraee, S. ♦ Safaryazdi, Z. ♦ Mahmoodzadeh, E.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Natural sciences & mathematics ♦ Physics ♦ Electricity & electronics
Subject Keyword Image coding ♦ Image segmentation ♦ Prediction methods ♦ Microscopy ♦ Image generation ♦ DNA ♦ Genetics ♦ Image storage ♦ Image reconstruction ♦ Image edge detection ♦ Compression ♦ HCS ♦ RNAi ♦ Predictors
Abstract In this paper a new prediction method is proposed for compression of RNAi images. The large number of RNAi images that are produced, from experiments on biological cells for diagnosis and prognosis of diseases, require special compression methods. Images are segmented so that the boundaries of the cells are recognized from the smooth areas. The proposed scheme adaptively changes its function to exploit the spatial features of the cell boundaries and the smooth regions. The proposed predictor has either better performance and comparable complexity, or it has lower complexity and comparable performance, when compared to the existing predictors for this specific application.
Description Author affiliation: Department of Electrical and Computer Engineering, Isfahan University of Technology, Iran (Karimi, N.; Samavi, S.; Amraee, S.; Safaryazdi, Z.; Mahmoodzadeh, E.) || Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada (Shirani, S.)
ISBN 9781424435098
ISSN 08407789
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2009-05-03
Publisher Place Canada
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 545.82 kB
Page Count 4
Starting Page 987
Ending Page 990

Source: IEEE Xplore Digital Library