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Optimizing Wavelet based Medical Image De-Noising

Author : Jagdeep Kaur and Ruchika Manchanda

Pages : 524-526
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Application of image processing in the area of medical sciences have revolutionized the diagnosis and treatment procedure. X-rays and ultrasound are considered to be the basic diagnosis tools in medical science. With the introduction of imaging in medical science, a great opportunity of research started in this area. New and advance algorithms are developed day by day to improve the quality of service these techniques give. An area of image restoration by denoising is also a field. Different algorithms are present to denoise an image corrupted by noise. In this paper we present a technique to optimize the denoising method using wavelets. Denoising in wavelet transform is controlled by threshold and level of decomposition. Here in this paper we present an analysis to determine the best suitable parameter of algorithm for implementation of wavelets. The main aim of image de-noising techniques is to remove noise while retaining as much as possible the important detail features. At the end we will discuss how de-noising techniques can be optimized using the thresholding parameter and varying the levels of decomposition.

Keywords: De-noising, wavelets, image processing, decomposition, thresholding

Article published in International Journal of Current Engineering and Technology, Vol.5, No.1 (Feb-2015)


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