Medical ultrasound image compression using joint optimization of thresholding quantization and best-basis selection of wavelet packets

This paper introduces an efficient image-coding algorithm using wavelet packets. The algorithm combines the top-down search approach with an operational rate-distortion (R-D) cost function to select the best wavelet packet basis at low-computational cost. The proposed method jointly optimizes the best-basis selection, coefficient “thresholding” and quantizer selection within the minimum description length (MDL) framework to develop a wavelet packet image coder named as JTQ-WP. We present results to verify the usefulness and versatility of this adaptive image coder both on medical US-images and natural images. The experimental results show that the joint optimization has a dramatic effect on the compression performance of medical ultrasound images. To further demonstrate the potential performance of the proposed method in comparison with the current state-of-the-art image coding algorithms, the results on Barbara image are also presented. The results show a coding gain of 0.91 dB over the benchmark wavelet-coding algorithm, SPIHT, on the Barbara image at a bit-rate of 0.25 bpp.