Application of maximum entropy-based image resizing to biomedical imaging

Pingli Billy Kao, Brian Nutter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Subsampling algorithms are applied to resize digital images to a lower resolution for display and transmission applications where the pixel count of the display mechanism is lower than the pixel count of the image acquisition method. Unfortunately, interpolation-based resizing methods change the color information and attenuate a specific range of high-frequency components from which the human visual system derives significant response. The described maximum entropy algorithm (MEA) provides that, as an image goes through subsampling, locally informative pixels are retained by analyzing the pixel neighboringhoods. The selected pixels are inserted directly in the output image, and color information is therefore preserved. From subjective observation and object evaluation using the entropy, contrast, and PSNR, MEA effectively maintains important features and color information and demonstrates better resizing performance than interpolation-based methods for some applications. Furthermore, the computational expense is suitable for real-time implementation.

Original languageEnglish
Title of host publicationProceedings - 19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages813-819
Number of pages7
ISBN (Print)0769525172, 9780769525174
DOIs
StatePublished - 2006
Event19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006 - Salt Lake City, UT, United States
Duration: Jun 22 2006Jun 23 2006

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
Volume2006
ISSN (Print)1063-7125

Conference

Conference19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
CountryUnited States
CitySalt Lake City, UT
Period06/22/0606/23/06

Fingerprint Dive into the research topics of 'Application of maximum entropy-based image resizing to biomedical imaging'. Together they form a unique fingerprint.

  • Cite this

    Kao, P. B., & Nutter, B. (2006). Application of maximum entropy-based image resizing to biomedical imaging. In Proceedings - 19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006 (pp. 813-819). [1647671] (Proceedings - IEEE Symposium on Computer-Based Medical Systems; Vol. 2006). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS.2006.46