Performance Evaluation of Selected Noise Removal Algorithms in Sickle Cell Images

Fenwa O.D., Ajala F.A and Adedeji O.T.

Abstract The impact of digital image processing is increasing by the day for its use in the medical and research areas. Proper identification of diseases is very crucial step for curing disease. In many cases microscopic analysis of peripheral blood samples by medical practitioner is an important test in the procedures for the diagnosis of any blood related disease and accurate diagnosis of disease is crucial for curing and controlling that disease. Some of the developed expert systems diagnosing various diseases using digital images of blood samples were prone to a variety of types of noise which affect image acquisition process that result in pixel values that do not reflect the true intensities of the real scene. The presence of noise in an image could result into wrong and incorrect information which could have possible consequence on the given image. Hence there is need for proper and adequate removal of noise during processing of images so as to obtain valuable and important information necessary for classification and diagnosis. In this paper, a comparison of performance of three selected noise removal algorithms (Median filter Ordinary filter and Weiner filter) was carried out on sickle cell images. The results revealed that the median filter showed high performance accuracy than the other filter types. Keyword:- Image processing, Sickle Cell, Median filter, Ordinary filter, Weiner filter

Title:	Performance Evaluation of Selected Noise Removal Algorithms in Sickle Cell Images
Author Name:	Fenwa O.D., Ajala F.A and Adedeji O.T.
Abstract:	Abstract The impact of digital image processing is increasing by the day for its use in the medical and research areas. Proper identification of diseases is very crucial step for curing disease. In many cases microscopic analysis of peripheral blood samples by medical practitioner is an important test in the procedures for the diagnosis of any blood related disease and accurate diagnosis of disease is crucial for curing and controlling that disease. Some of the developed expert systems diagnosing various diseases using digital images of blood samples were prone to a variety of types of noise which affect image acquisition process that result in pixel values that do not reflect the true intensities of the real scene. The presence of noise in an image could result into wrong and incorrect information which could have possible consequence on the given image. Hence there is need for proper and adequate removal of noise during processing of images so as to obtain valuable and important information necessary for classification and diagnosis. In this paper, a comparison of performance of three selected noise removal algorithms (Median filter Ordinary filter and Weiner filter) was carried out on sickle cell images. The results revealed that the median filter showed high performance accuracy than the other filter types. Keyword:- Image processing, Sickle Cell, Median filter, Ordinary filter, Weiner filter
Cite this article:	Fenwa O.D., Ajala F.A and Adedeji O.T. , " Performance Evaluation of Selected Noise Removal Algorithms in Sickle Cell Images " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 4, Issue 1, January - February 2015 , pp. 001-005 , ISSN 2278-6856.
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