Novel superimposed diamond search algorithm for medical image compression
by T.M.P. Rajkumar; Mrityunjaya V. Latte
International Journal of Computer Applications in Technology (IJCAT), Vol. 51, No. 3, 2015

Abstract: A novel search algorithm called superimposed diamond search algorithm (SDSA) based on lifting wavelet transform (LWT) for medical image compression is proposed in this paper. Fuzzy C means clustering (FCM) is applied to extract the region of interest (ROI) from the medical image. MAXSHIFT method is used to scale the coefficients so that the bits associated with the ROI are placed in higher bit planes than the bits associated with the background without the requirement of the shape information and without the need for calculating the ROI mask. SDSA keeps track of significant pixels of wavelet sub-band in hexagonal search in the scan order of left to right and top to bottom. The experimental results show the good compression ratio over the other existing methods such as set partitioning in hierarchical trees (SPIHT) and embedded zerotree wavelet (EZW).

Online publication date: Wed, 13-May-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com