Effects of various De-Speckling Filters on Brachial Plexus Ultrasound Imaging
Ankur Bhardwaj1, Sanmukh Kaur2, Anand Prakash Shukla3, Manoj Kumar Shukla4 

1Ankur Bhardwaj, Scholar, Department of Computer Science & Engineering, Amity University, Noida (U.P), India.
2Sanmukh Kaur, Associate Professor, (Guide), Department of Electronics & Communication, Amity University, Noida (U.P), India.
3Anand Prakash Shukla, Professor, (Co-Guide), Department of Computer Science & Engineering, KIET Group of Institutions, Ghaziabad (U.P), India
4Manoj Kumar Shukla, Associate Professor (Co-Guide), Department of Computer Science & Engineering, Amity University, Noida (U.P), India.

Manuscript received on 16 March 2019 | Revised Manuscript received on 21 March 2019 | Manuscript published on 30 July 2019 | PP: 5058-5065 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1631078219/19©BEIESP | DOI: 10.35940/ijrte.B1631.078219
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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: Medical Ultrasound images are generally corrupted by Speckle noise. It deteriorates the quality of ultrasound imaging and video that makes it difficult to observe visually. Because of which resolution and contrast of the image is reduced. Despeckling of medical US images is an important process for diagnostic of disease. In this paper effect of various existing despeckling filter on ultrasound images has been studied. All the filters have been implemented in a framework and result are observed in the form of various parameters such as GAE, MSE, SNR, SRMSE, PSNR, UIQI, SSIM, AD, SC, MD. The results obtained have been used for statistically comparing the performance of the filters. It is also analyzed that which type of filters are more suited for particular type of images, noise and other conditions. This will also provide guidelines for the researchers for designing of new filters in future.
Index Terms: Mean Square Error, Peak Signal to Noise Ratio, Speckle Noise, Structural Similarity Index Measure.

Scope of the Article: Signal and Image Processing