Adaptive Gabor image transformation: application in scientific visualization

This paper addresses the issues of compression and computation efficiency of transform-based image compression methods. Most transform-based compression systems operate based on the assumption that the input images are mostly conventional types of images. We argue that these systems will not perform efficiently in some image domains in which the aforementioned assumption does not hold. We believe an image encoding system must take into consideration the directional and frequency attributes in the input images in order to achieve high encoding quality. In this paper, we present a novel adaptive approach for image transformation. Experimental results show that for an 'unconventional' image, the proposed system produces better image quality than JPEG at the same bit-rates.