Title :
Evolving improved transforms for reconstruction of quantized ultrasound images
Author :
Miller, Chris ; Babb, Brendan ; Moore, Frank ; Peterson, Michael
Author_Institution :
Math. Sci. Dept., Univ. of Alaska Anchorage, Anchorage, AK, USA
Abstract :
State-of-the-art lossy compression schemes for medical imagery utilize the 9/7 wavelet. Recent research has established a methodology for using evolutionary computation (EC) to evolve wavelet and scaling numbers describing novel reconstruction transforms that outperform the 9/7 under lossy conditions. This paper describes an investigation into whether evolved transforms could automatically compensate for the detrimental effects of quantization for ultrasound (US) images. Results for 16:1, 32:1, and 64:1 quantization consistently demonstrate superior performance of evolved transforms in comparison to the 9/7 wavelet; in general, this advantage increases in proportion to the selected quantization level.
Keywords :
biomedical ultrasonics; image coding; image reconstruction; medical image processing; quantisation (signal); ultrasonic imaging; wavelet transforms; evolutionary computation; image quantization; image reconstruction; lossy compression schemes; medical imagery; quantized ultrasound images; wavelet transforms; Biomedical imaging; Image coding; Image reconstruction; Multiresolution analysis; Quantization; Wavelet transforms;
Conference_Titel :
Applications of Computer Vision (WACV), 2011 IEEE Workshop on
Conference_Location :
Kona, HI
Print_ISBN :
978-1-4244-9496-5
DOI :
10.1109/WACV.2011.5711511
