Compression of ultrasound images using wavelet based space-frequency partitions

Authors

  • 1Senior programmer Noor Abdulmuttaleb Jaafar Al-Muqdad College of Education, Diyala University,
  • Senior programmer Hind Ibrahim Mohammed Al-Muqdad College of Education, Diyala University,
  • Senior programmer Abbass Alaa Mahdi Al-Muqdad College of Education, Diyala University,

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.

Downloads

Published

2018-04-30

How to Cite

Abdulmuttaleb Jaafar, 1Senior programmer N., Hind Ibrahim Mohammed, S. programmer, & Abbass Alaa Mahdi, S. programmer. (2018). Compression of ultrasound images using wavelet based space-frequency partitions. International Journal of Engineering Technology and Computer Research, 6(2). Retrieved from https://ijetcr.org/index.php/ijetcr/article/view/473

Issue

Section

Articles