DEVELOP FILTERING AND THRESHOLDING ALGORITHM WHICH GIVES BETTER PERFORMANCE IN BOTH MODERATE AND HIGH NOISE LEVEL

Noise is always a component of every picture that has been acquired from its original source. Images have been de-noised using a number of different techniques in the past. Image denoising may still be improved. In this research, we take a look at the various available denoising techniques, including the filtering approach and the wavelets-based approach, and compare them using bilateral filters. Noise is inherently confined throughout the acquiring and transmitting of images. That's why enhancing picture quality through denoising processing is essential. In general, all algorithms make use of filtering and thresholding settings. How to optimally adjust these settings in denoising algorithms depends on a number of factors, including the types of pictures to be processed. Parameter determination methods abound, and each one is best suited to a certain scenario.