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Performance Analysis of VTV, NLM and BM2D Techniques for Denoising an Image

V. Rabila, G. Bharatha Sreeja


In this paper, three different types of denoising algorithms are analyzed for the noise removal of an image. The methods are Vectorial Total Variation (VTV), Non-Local Means (NLM) algorithm, Block Matching and 2D Filtering (BM2D). Chambolle’s projection algorithm is used to denoise an image in VTV method. In NLM method, Non-Local Means algorithm is used to remove the noise and preserves the fine details. NLM algorithm is an algorithm for image denoising which takes the mean value of group of pixels. In BM2D method, image is divided into number of blocks. Here, similar blocks are grouped together and stored in a 2D array and affine transformation is applied to a 2D array because affine transformation preserves points, straight lines and planes. The affine transformation technique is typically used to correct the geometric distortions. Wiener filtering is applied for the transformed image. Then, inverse affine transformation is applied at the final step. The performance of three methods are evaluated by calculating the parameters such as PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and Elapsed time.

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