Performance Analysis of Spatial and Transform Filters for Efficient Image Noise Reduction Santosh Paudel Ajay Kumar Shrestha Pradip Singh Maharjan Rameshwar Rijal Computer and Electronics Computer and Electronics Computer and Electronics Computer and Electronics Engineering Engineering Engineering Engineering KEC, TU KEC, TU KEC, TU KEC, TU Lalitpur, Nepal Lalitpur, Nepal Lalitpur, Nepal Lalitpur, Nepal
[email protected] [email protected] [email protected] [email protected] Abstract—During the acquisition of an image from its systems such as laser, acoustics and SAR (Synthetic source, noise always becomes integral part of it. Various Aperture Radar) images [3]. algorithms have been used in past to denoise the images. Image denoising still has scope for improvement. Visual This paper introduces different types of noise to be information transmitted in the form of digital images has considered in an image and analyzed for various spatial become a considerable method of communication in the and transforms domain filters by considering the image modern age, but the image obtained after transmission is metrics such as mean square error (MSE), root mean often corrupted due to noise. In this paper, we review the squared error (RMSE), Peak Signal to Noise Ratio existing denoising algorithms such as filtering approach (PSNR) and universal quality index (UQI). and wavelets based approach, and then perform their comparative study with bilateral filters. We use different II. BACKGROUND noise models to describe additive and multiplicative noise The Wavelet Transform (WT) is a powerful tool of in an image. Based on the samples of degraded pixel signal and image processing, which has been neighborhoods as inputs, the output of an efficient filtering successfully used in many scientific fields such as signal approach has shown a better image denoising performance.