METHODOLOGIES BASED ON COMPREHENSIVE FILTER APPROACH TO DETERMINING IMAGE FILTERING & NOISE CANCELLATION
In microscopy, digital image processing has become popular. The classification of cells is done using advanced techniques. The digital image processing techniques that can be used to detect abnormalities in an image can be applied to detect them. Preprocessing is essential since noise will interfere with image processing techniques. Image filtering to remove noise is the first step. This paper, introduce filters to denoise microscopic images based on the accuracy of denoising. This paper compares two filter types - Wiener and Median filters - in their ability to denoise the image in the first stage of preprocessing. During the later stages, data were compared to better categorize the images based on peak signal-to-noise (PSNR) between the Wiener filter and the Median filter. Gaussian noise was present in more than 35 real-time images, a median filter provided higher PSNR than a Wiener filter.
Gaussian Noise, Image Processing, Median Filter, PSNR, Wiener Filter