Abstract
SummaryIn Medical Image Processing (MIP), the images are influenced by various types of noises. Hence, reducing such noises becomes a crucial issue. The main objective is to denoise the noisy images effectively with reduced computational cost. This paper proposes a denoising technique using Discrete Wavelet Transform (DWT) and Social Spider Optimization (SSO) algorithm. Initially, DWT is applied over various noises over the input medical images. Then, the wavelet coefficients are optimized by applying the SSO algorithm. Finally, the inverse of DWT (IDWT) is applied over the optimized coefficients. The denoised image is obtained, and then, the PSNR evaluation is utilized for finding the superior performance. Experimental results using MATLAB show that the proposed algorithm has better performance when compared with the existing approaches.
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