Adaptive Thresholding Method for Speckle Reduction of Echocardiographic Images

Abstract

Speckle noise is a granular disturbance, which is an inherent property in echocardiographic images. One of the most powerful and efficient tools for despeckling of images is wavelet transform. A literature survey conducted reveals many wavelet-based thresholding techniques are developed based on universal or level adaptive methods. To find the optimum threshold is a key point in speckle reduction. This paper shows the comparison of different thresholding techniques with proposed adaptive thresholding technique in terms of peak signal to noise ratio (PSNR), structural similarity measure index (SSIM), image quality index (IQI) and edge preservation index (EPI). The qualitative evaluation is done by using residuals. The processing time is also measured for different algorithms. The obtained results indicate that the proposed thresholding technique gives better performance in most of performance measurement parameters.

KEYWORDS:

• Echocardiographic images
• Speckle noise
• Thresholding
• Wavelet transform

Additional information

Notes on contributors

Pallavi Kulkarni

Pallavi Kulkarni received her Bachelor of Engineering from Shivaji University, Maharashtra, India in 2009. She has completed her Master of Engineering degree in electronics and communication engineering from the Pune University, Maharashtra, India in 2012. Her research project in masters was on biomedical signal processing using wavelet transform by using Xilinx system generator. Since 2012 she has been working as an associate professor in electronics and communication engineering. She is currently pursuing PhD from Vellore Institute of Technology, Tamilnadu, India. Her area of research includes echocardiographic image processing, segmentation and noise reduction, wavelet transform. Email: [email protected]

Deepa Madathil

Deepa Madathil currently works as an associate professor in the Department of Sensor and Biomedical Technology in School of Electronics Engineering at VIT, Vellore. She has a bachelors in biomedical engineering from JNTU, Hyderabad; Masters in biomedical informatics from Arizona State University, USA and a PhD in bioinformatics from VIT University, Vellore. While getting her masters she was also working at St. Joseph’s Hospital and Medical Center, Phoenix, USA as a Systems Analyst. After her masters, Dr Deepa worked as a Research Analyst and a Biostatistician at Banner Health Hospital and Medical Center, Phoenix, USA.