We show that the popular Non-Local Means method for image denoising can be implemented exactly, easily and with lower computation time using convolutions. Also, our algorithm allows the use of infinite-size non-binary patches, which improves the denoising quality.

Diffusion tensor imaging (DT-MRI) is very sensitive to corrupting noise due to the non linear relationship between the diffusion-weighted image intensities (DW-MRI) and the resulting diffusion tensor. Denoising is a crucial step to increase the quality of the estimated tensor field. This enhanced quality allows for a better quantification and a better image interpretation. The methods proposed ...

The classical non-local means image denoising approach, the value of a pixel is determined based on the weighted average of other pixels, where the weights are determined based on a fixed isotropic ally weighted similarity function between the local neighbourhoods. It is demonstrate that noticeably improved perceptual quality can be achieved through the use of adaptive anisotropic ally weighted...

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-range dependencies. Inspired by the classical non-local means method [4] in computer vision, our non-local operation computes the response at a position as a weighted sum of the fea...

The unavoidable speckle in SAR images seriously interferes with image quality and has a negative effect on subsequent interpretation. existing filters still need to be strengthened terms of both noise suppression edge preservation. Based this, novel non-local means filter by multi-directional local plane inclination angle (MDLPIA) is proposed. proposed uses the MDLPIA reconstruct new weight fun...

We propose an adaptive approach for ‘non local means (NLM)’image filtering termed as ‘non local adaptive clipped means (NLACM)’, which reduces the effect of outliers and improves the denoising quality as compared to traditional NLM. Common method to neglect outliers from a data population is computation of mean in a range defined by mean and standard deviation. In NLACM we perform the median wi...

The speckle is omnipresent in synthetic aperture radar (SAR) images as an intrinsic characteristic. However, it is unwanted in certain applications. Therefore, intelligent filters for speckle reduction are of great importance. It has been demonstrated in several literatures that the non-local means filter can reduce noise while preserving details. This paper discusses non-local means filter for...