Madan Lal

Work place: Department of Computer Engineering, Punjabi University, Patiala. India

E-mail: madanlal@pbi.ac.in

Website:

Research Interests: Image Processing, Image Manipulation, Image Compression, 2D Computer Graphics, Computer Graphics and Visualization, Computer systems and computational processes

Biography

Madan Lal has received a Bachelor of Technology degree in Computer Science and Engineering from Guru Nanak Dev University, Amritsar in 1998 and M.Tech. Degree in Computer Engineering from Punjabi University, Patiala in 2007. Currently he is pursuing Ph.D. from Punjabi University, Patiala. His research interests are in Computer Graphics and Digital Image Processing.

Author Articles
Speckle Reduction with Edge Preservation in B-Scan Breast Ultrasound Images

By Madan Lal Lakhwinder Kaur Savita Gupta

DOI: https://doi.org/10.5815/ijigsp.2016.09.08, Pub. Date: 8 Sep. 2016

Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence makes the visual inspection difficult. In addition, it limits the professional application of image processing techniques such as automatic lesion segmentation. So speckle reduction is an essential step before further processing of ultrasonic images. Numerous techniques have been developed to preserve the edges while reducing speckle noise, but these filters avoid smoothing near the edges to preserve fine details. The objective of this work is to suggest a new technique that enhances B-Scan breast ultrasound images by increasing the speckle reduction capability of an edge sensitive filter. In the proposed technique a local statics based filter is applied in the non homogeneous regions, to the output of an edge preserving filter and an edge map is used to retain the original edges. Experiments are conducted using synthetic test image and real time ultrasound images. The effectiveness of the proposed technique is evaluated qualitatively by experts and quantitatively in terms of various quality metrics. Results indicate that proposed method can reduce more noise and simultaneously preserve important diagnostic edge information in breast ultrasound images. 

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