Open AccessMEDICAL IMAGES COMPRESSION BASED ON SPIHT AND BAT INSPIRED ALGORITHMS
Author(s) -
Sarah Saadoon Jasim
Publication year - 2019
Publication title -
al-mağallaẗ al-ʿirāqiyyaẗ li-l-ḥāsibāt wa-al-maʿlūmāt/iraqi journal for computers and informatics
Language(s) - English
Resource type - Journals
eISSN - 2520-4912
pISSN - 2313-190X
DOI - 10.25195/ijci.v45i1.43
Subject(s) - lossy compression , lossless compression , set partitioning in hierarchical trees , computer science , discrete cosine transform , image compression , algorithm , data compression , compression ratio , compression (physics) , data compression ratio , texture compression , region of interest , artificial intelligence , image processing , image (mathematics) , materials science , engineering , composite material , internal combustion engine , automotive engineering
There is a significant necessity to compress the medical images for the purposes of communication and storage.Most currently available compression techniques produce an extremely high compression ratio with a high-quality loss. Inmedical applications, the diagnostically significant regions (interest region) should have a high image quality. Therefore, it ispreferable to compress the interest regions by utilizing the Lossless compression techniques, whilst the diagnostically lessersignificant regions (non-interest region) can be compressed by utilizing the Lossy compression techniques. In this paper, a hybridtechnique of Set Partition in Hierarchical Tree (SPIHT) and Bat inspired algorithms have been utilized for Lossless compressionthe interest region, and the non-interest region is loosely compressed with the Discrete Cosine Transform (DCT) technique.The experimental results present that the proposed hybrid technique enhances the compression performance and ratio. Also,the utilization of DCT increases compression performance with low computational complexity.