Speckle Noise Reduction from Medical Images Using Gaussian Fuzzy Membership Function

The primary concept of this paper is a fuzzy membership function-based filter with the expertise to reduce speckle noise that is often utilized in clinical diagnosis such as ultrasonography. In medical science, image sharpening is a highly effective approach for recognizing human inner organs and body tissues. Speckle noise is multiplicative in nature and it highly affects the image and reduces some useful information. The target of image noise reduction is to extract the genuine image from a noisy speckled image. In this paper, a Gaussian fuzzy-based system has been developed that is fast and provides good accuracy depending upon the membership function. Also, experimental results demonstrate that the proposed algorithm ensures better filtering quality and image restoration ability in comparison with others.