A Hybrid Neural Filter (HNF) Based on Adaptive Median and Weiner Techniques for Reducing Speckle Noise of Ultrasound Liver Tumor Images
Deepak S Uplaonkar1, Basavaraj Amarapur2

1Deepak S Uplaonkar*, Department of Computer Engineering, JSPM Narhe Technical Campus, Pune, Maharashtra, India.
2Dr. Basavaraj Amarapur, Department of Electrical and Electronics Engineering, Poojya Doddappa Appa college of Engineering Kalaburagi, Karnataka, India. 

Manuscript received on 2 August 2019. | Revised Manuscript received on 9 August 2019. | Manuscript published on 30 September 2019. | PP: 2243-2250 | Volume-8 Issue-3 September 2019 | Retrieval Number: B3252078219/19©BEIESP | DOI: 10.35940/ijrte.B3252.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Pre-processing of image is considered to be an important aspect medical image analysis in order to enhance its quality. Noise reduction is performed for improvement in the visual quality and removing redundant image values. Ways of pre-processing of image are a necessity, for removing the noise and for quality enhancement of the image. Before applying any approach on medical images, measures used to pre-process seem to be vital for limiting the abnormalities’ findings with no influence from background of the medical image. In this work, a filter is proposed based on Adaptive Median and Weiner Hybrid Neural Filter for noise reduction. The review of filtering techniques is implemented using MATLAB platform, followed by comparison of results with different filtering techniques to show the system effectiveness.
Keywords: Speckle Noise, Median Filter, Weiner Filter, Hybrid Neural Filter.

Scope of the Article:
Neural Information Processing