Compression of ultrasound images using wavelet based space-frequency partitions

Abstract

This paper describes the compression of grayscale medical ultrasound images using a new compression technique, space-frequency segmentation. This method finds the rate-distortion optimal representation of an image from a large set of possible space-frequency partitions and quantizer combinations. The method is especially effective when the images to code are statistically inhomogeneous, which is the case for medical ultrasound images. We implemented a real compression algorithm based on this method, and applied the resulting algorithm to representative ultrasound images. The result is an effective technique that performs significantly better than a current leading wavelet transform coding algorithm, Set Partitioning In Hierarchical Trees (SPIHT), using the standard objective PSNR distortion measure. KEYWORDS: Ultrasound image compression, wavelet packets, space-frequency segmentation.