Title :
SVBS: a high-resolution medical image compression algorithm using slicing with variable block size segmentation
Author :
Namuduri, K.R. ; Ranganathan, N. ; Rashedi, Hooman
Author_Institution :
GTE Telecommun. Services Inc., Tampa, FL, USA
Abstract :
Medical images such as mammograms and chest X-rays require resolution of the the order of 4096×4096 pixels with 10 to 16 bits per pixel. Because of the poor visualization and extreme sensitive nature of the information content, any information loss in storage and retrieval of medical information may not be acceptable. In this paper, an efficient lossless image compression scheme is proposed for high resolution medical images. The proposed method is based on two concepts: multibit plane slicing and variable block segmentation. It exploits the two basic image characteristics smoothness and similarity to achieve high compression efficiency. The proposed algorithm is applied to 12 and 16 bit mammogram images. The compression efficiency of the proposed algorithm is better than that obtained by other lossless compression schemes including the scheme based on the JPEG standard
Keywords :
data compression; diagnostic radiography; image coding; image segmentation; medical image processing; chest X-rays; efficiency; lossless image compression; mammograms; medical image compression; multibit plane slicing; variable block size segmentation; Biomedical imaging; Content based retrieval; Image coding; Image resolution; Image segmentation; Information retrieval; Pixel; Transform coding; Visualization; X-rays;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547302