A speckle reduction and characteristic enhancement algorithm to ultrasonic image based on wavelet technology

Yue Qin Li, Jin Ping Li, Lei Han*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The inherent characteristic of ultrasonic and the application environment make ultrasonic image have some defects: image with speckle noise, edge blur and low contrast. In order to reduce the speckle noise and enhance the image characteristics, a speckle reduction and characteristic enhancement anisotropic diffusion algorithm is proposed based on the wavelet technology in this paper. The algorithm and parameters choice and algorithm realization steps had been analyzed and illuminated particularly. A compare research experiment for real ultrasonic image has been done using the algorithm and other traditional methods. The experimental result indicates that the proposed algorithm has strong speckle reduction and enhancement image ability. The purpose of removing speckle noise and enhancing image characteristics at same time has been reached.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010
Pages135-138
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010 - Haiko, China
Duration: 11 Nov 201012 Nov 2010

Publication series

NameProceedings - 2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010
Volume1

Conference

Conference2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010
Country/TerritoryChina
CityHaiko
Period11/11/1012/11/10

Keywords

  • Anisotropic diffusion
  • Characteristic enhancement
  • Speckle noise
  • Ultrasonic image
  • Wavelet

Fingerprint

Dive into the research topics of 'A speckle reduction and characteristic enhancement algorithm to ultrasonic image based on wavelet technology'. Together they form a unique fingerprint.

Cite this