TY - GEN
T1 - Application of maximum entropy-based image resizing to biomedical imaging
AU - Kao, Pingli Billy
AU - Nutter, Brian
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33845595904&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2006.46
DO - 10.1109/CBMS.2006.46
M3 - Conference contribution
AN - SCOPUS:33845595904
SN - 0769525172
SN - 9780769525174
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 813
EP - 819
BT - Proceedings - 19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
Y2 - 22 June 2006 through 23 June 2006
ER -