We propose a new class of non-linear image recovery operators based on local smoothing applied both in the spatial domain (horizontal smoothing) and in the gray-level domain (vertical smoothing). The commonly used horizontal smoothing gives the way of reducing the noise level (noise filtering), whereas the vertical smoothing yields the edge preservation property. The method is indexed by a real...

An efficient noise treatment scheme has been developed to achieve low-dose CT diagnosis based on currently available CT hardware and image reconstruction technologies. The scheme proposed includes two main parts: filtering in sinogram domain and smoothing in image domain. The acquired projection sinograms were first treated by our previously proposed Karhunen-Loeve (K-L) domain penalized weight...

We demonstrate how one can choose the smoothing parameter in image denoising by a statistical multiresolution criterion, both globally and locally. Using inhomogeneous diffusion and total variation regularization as examples for localized regularization schemes, we present an efficient method for locally adaptive image denoising. As expected, the smoothing parameter serves as an edge detector i...

Smoothing filter is the method of choice for image preprocessing and pattern recognition. We present a new concurrent method for smoothing 2D object in binary case. Proposed method provides a parallel computation while preserving the topology by using homotopic transformations. We introduce an adapted parallelization strategy called split, distribute and merge (SDM) strategy which allows effici...

The aim of the project is to detect and classify the brain tumor from MRI image. This project involves mainly 6 stages namely Input Image, Preprocessing, Segmentation, Post Processing, Feature Extraction and Classification. In this phase, 4 stages are implemented, Input image, preprocessing, segmentation and post processing. Input image reads the MRI brain image. Preprocessing mainly includes i...

Ultrasound imaging is an important technique with great potential for accurate nondestructive testing. Previously, we proposed a high-resolution 3-D imaging algorithm for UWB radar, the Envelope algorithm with adaptive smoothing techniques. The Envelope imaging algorithm utilizes the principle that the target boundary is expressed as an envelope of spheres determined by observed ranges, while t...

Edge detection algorithms have traditionally utilized the Gaussian Linear Filter (GLF) for image smoothing. Although GLF has very good properties in removing noise and unwanted artifacts from an image, it is also known to remove many valid edges. To cope with this problem, edge preserving smoothing filters have been proposed and they have recently attracted increased attention. In this paper, w...

Anisotropic diffusion has been widely used in image processing for its efficiency of smoothing the noisy images while preserving the sharp edges. In this paper we will explore a general version of anisotropic diffusion schemes for vectorvalued images, based on the polar-coordinate representation of the vectors. As an example, we will apply our method to color images and show its ability of edge...

Bilateral filtering is widely used to enhance photographic images, but in most implementations is poorly suited to seismic images. A bilateral filter consists of two filter kernels. By replacing one of those kernels with a smoothing filter that conforms to image structures, we obtain a bilateral filter suitable for seismic image processing. Examples and comparison with conventional edge-preserv...

We examined the statistical performance of clustering single particle molecular images by bottom-up clustering, a hierarchical algorithm, using simulated protein images with a low signal-to-noise ratio. Using covariance for the measure of similarity together with the iterative alignment, our method was found to be fairly robust against noise. Clustering tests of four known protein structures we...