In the past two decades, many noise reduction techniques have been developed for removing noise and retaining edge details in images. The process of removing noise from the original image is still a demanding problem for researchers. There have been several algorithms and each has its assumptions, merits, and demerits. The prime focus of this paper is related to the pre processing of an image before it can be used in applications. The pre processing is done by de-noising of images. In order to achieve these de-noising algorithms, filtering approach and wavelet based approach are used and performs their comparative study. Image filtering algorithms are applied on images to remove the different types of noise that are either present in the image during capturing or injected into the image during transmission. Wavelet transform and median filter are used for the image reconstruction and denoising. In this paper, we propose fast and high-quality nonlinear algorithms for denoising digital images corrupted by mixed Poisson-Gaussian noise.
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