A Fuzzy Rule based Hybrid Approach for Speckle Reduction in Digital Images
In this paper, a method is proposed to eliminate speckle noise which usually affects medical images such as ultrasounds and Synthetic Aperture Radar (SAR) images. Speckle noises are multiplicative in nature. Noise removal is one of the most important steps in the field of image processing as it removes unwanted data and preserves information from the images that are actually useful. The method used in this experiment works in two phases. The first phase uses a fuzzy inference system to classify the image into various regions using coefficient of variance and gradient magnitude as inputs and the second phase involves applying different fuzzy based filters to the regions so as to provide edge preservation while suppressing speckle noise. Fuzzy logic based technique is used because of its ability to accommodate inexact and approximate data instead of crisp values. The results of the experiment are evaluated using metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM).
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