Bit-plane-channelized hotelling observer for predicting task performance using lossy-compressed images

Brian M. Schmanske; Murray H. Loew

doi:10.1117/12.480082

22 May 2003 Bit-plane-channelized hotelling observer for predicting task performance using lossy-compressed images

Brian M. Schmanske, Murray H. Loew

Proceedings Volume 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment; (2003) https://doi.org/10.1117/12.480082
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

A technique for assessing the impact of lossy wavelet-based image compression on signal detection tasks is presented. A medical image’s value is based on its ability to support clinical decisions such as detecting and diagnosing abnormalities. Image quality of compressed images is, however, often stated in terms of mathematical metrics such as mean square error. The presented technique provides a more suitable measure of image degradation by building on the channelized Hotelling observer model, which has been shown to predict human performance of signal detection tasks in noise-limited images. The technique first decomposes an image into its constituent wavelet subband coefficient bit-planes. Channel responses for the individual subband bit-planes are computed, combined,and processed with a Hotelling observer model to provide a measure of signal detectability versus compression ratio. This allows a user to determine how much compression can be tolerated before signal detectability drops below a certain threshold.

Citation Download Citation

Brian M. Schmanske and Murray H. Loew "Bit-plane-channelized hotelling observer for predicting task performance using lossy-compressed images", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); https://doi.org/10.1117/12.480082

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