Optimal restoration of compressed biomedical images: a discrete lattice theoretic approach

Vivek Swarnakar; Athimootil V. Mathew; Edward R. Dougherty; Claudio H. Sibata

doi:10.1117/12.237949

16 April 1996 Optimal restoration of compressed biomedical images: a discrete lattice theoretic approach

Vivek Swarnakar, Athimootil V. Mathew, Edward R. Dougherty, Claudio H. Sibata

Proceedings Volume 2710, Medical Imaging 1996: Image Processing; (1996) https://doi.org/10.1117/12.237949
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

Biomedical image data, such as obtained from CT or MR imaging modalities, tend to occupy a large amount of storage space. At the cost of losing or distorting salient features, lossy compression techniques can be used to reduce significantly the amount of data storage space. The main aim of this article is to present a novel method for optimal enhancement and restoration of images recovered from data stored using lossy compression techniques. A statistical model of the deformations undergone by the salient features within the original image, when it is stored using lossy compression techniques and then recovered, is generated. This statistical model generates a discrete lattice space. The algorithm presented here designs a set of filters over the statistical lattice space. Due to the statistical nature of the lattice the designed filters are optimal and the best possible recovery of the salient features in the original image is achieved. Results comparing the performance of the presented method to that achieved by median filters are presented. Robustness of the algorithm is tested by applying filters generated using a set of images of one subject, to images of different subjects and images stored using different compression ratios.

Citation Download Citation

Vivek Swarnakar, Athimootil V. Mathew, Edward R. Dougherty, and Claudio H. Sibata "Optimal restoration of compressed biomedical images: a discrete lattice theoretic approach", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237949

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image compression

Digital filtering

Image filtering

Optimal filtering

Image processing

Berkelium

Switching

Show All Keywords

Keywords/Phrases

Search In:

Publication Years