Image smoothing and segmentation are fundamental tasks in Computer Vision and there are numerous algorithms that have been developed and applied to these tasks in various application domains. Several challenges remain unconquered. In this paper, we consider the challenge of achieving smoothing and segmentation while preserving complicated and detailed features present in the image, be it a gray...

A novel adaptive smoothing method is proposed for noise removal and feature preservation. Unlike the previous methods, we adopt two proposed measures to detect discontinuities in an image. Spatial variance is employed to form a measure for detecting contextual discontinuities that can be used for feature preservation and control of the smoothing speed, and another measure is proposed to detect ...

Voxel-based analysis (VBA) is commonly used for statistical analysis of image data, including the detection of significant signal differences between groups. Typically, images are co-registered and then smoothed with an isotropic Gaussian kernel to compensate for image misregistration, to improve the signal-to-noise ratio (SNR), to reduce the number of multiple comparisons, and to apply random ...

The pivotal research work that has been carried out and described in this literature acknowledges the importance of various smoothing techniques for processing 3D human faces from 2.5D range face images. The smoothing techniques have been developed and implemented using MATLAB-Simulink for real time processing in embedded system. In addition, the significance of smoothed 2.5D range image over o...

We present a comparative study of the effects of applying pre-processing and post-processing to remote sensing data both in the spatial image domain and the feature domain. We use a neural network for classification since it is not biased by a priori assumptions about the distributions of the spectral values of the classes. Spatial smoothing was applied both as preand post-processing steps. Pre...

and Applied Analysis 3 The flow u(t) = S(t)g is a continuous semigroup of contractions in H−1(Ω) in this case or in L(Ω), in other situation, and the denoising effect of (6) is due to smoothing effect of S(t) on initial data, a property which is a characteristic to semigroups generated by the nonlinear operators A of the gradient type ∂φ, where φ is a convex and lower semicontinuous function. S...

Impulsive noise filtering is an important problem of image processing. The problem of noise elimination is closely connected with the problem of maximal preservation of image edges. The requirement of maximal preservation of edges is especially important for images corrupted by impulsive noise with a low corruption rate. To avoid smoothing of the image during filtering, all noisy pixels must be...

This paper brings to the fore a set of masks that are used in combination to simulate the pattern-colour separability function of the human visual system. These kernels give a perceptual degree of smoothing which correspond to measurements estimated from human psychophysical experiments. We have found that they are a better approach to image smoothing for colour images than the traditional Gaus...

The problem of estimating feature orientation from noisy image data is addressed using a multiresolution technique. It is shown that by an appropriate choice of representation of orientation, it is possible to employ simple linear smoothing methods to reduce estimation noise. The smoothing is done using a combination of scale-space recursive filtering and iterative estimation, giving significan...

We present an algorithm developed particularly to detect gravitationally lensed arcs in clusters of galaxies. This algorithm is suited for automated surveys as well as individual arc detections. New methods are used for image smoothing and source detection. The smoothing is performed by so-called anisotropic diffusion, which maintains the shape of the arcs and does not disperse them. The algori...