An Optimized Hybrid Filter designing for Speckle and Gaussian Noise Reduction in Ultra-Sound Images

Abstract

Image which is a visual perception of a scene or something is a set of pixels that have certain values which appear in the form of colors to view that particular set of pixel as image. Image contains information about whatever is being depicted in the picture and hence it can be said as a useful source for storing or conveying information. Image noise is apparent in image region with low signal level, such as shadow region or under exposed images. The work presents the concept of noising and denoising in a digital image. Noise is a kind of disturbance that occurs in the channel at the time of transmission. Image denoising is the procedure of improving true images from the noisy images. For ages researchers have been proposing several techniques that were used to remove the noise from the image. Image denoising is the procedure of improving true image from the noisy image. At the time of such process it is difficult to reduce noise. Owing to this difficulty, numerous denoising models have been proposed [4]. The paper presents the reduction of speckle and Gaussian noise in the biomedical ultrasound images. In the proposed work, the Butterworth filter is applied for filtering the noisy image and then the coefficients are optimized by using the firefly algorithm mechanism to remove noise that occurs at the time of transmission and then it is hybrid with the Weiner filter. Experiments have been performed to check the performance of the proposed technique. The results are analyzed quantatively using PSNR and SSIM. The results are also evaluated on other performance parameters such as BER, MSE and fitness on speckle as well as on Gaussian noise.