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• W2777676579 abstract "Medical image processing plays a significant role in disease diagnosis and provides the details about tissues and organs. Image denoising techniques are used to restore the original information of the image and remove unwanted distortion. In this paper, denoising the clinical database image using discrete wavelet transform (DWT) is done and the performance is measured by considering the following quality metric parameters, namely peak signal-to-noise ratio, structural content, image fidelity, normalized correlation coefficient, structural similarity index, and universal quality index. We evaluate the performance of various wavelet filter coefficients for image denoising and which wavelet coefficient would be most reliable one on clinical dataset, and their efficiency is reported." @default.
• W2777676579 created "2018-01-05" @default.
• W2777676579 creator A5022354867 @default.
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• W2777676579 date "2017-12-22" @default.
• W2777676579 modified "2023-09-25" @default.
• W2777676579 title "Performance Analysis of Wavelet Function Using Denoising for Clinical Database" @default.
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• W2777676579 doi "https://doi.org/10.1007/978-981-10-4852-4_23" @default.
• W2777676579 hasPublicationYear "2017" @default.
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