This paper introduces the concept of image fusion of filtered noisy images for impulse noise reduction. Image fusion is the process of combining two or more images into a single image while retaining the important features of each image. Multiple image fusion is an important technique used in military, remote sensing and medical applications. Five different filtering algorithms are used individ...

Rician noise introduces a bias into MRI measurements that can have a significant impact on the shapes and orientations of tensors in diffusion tensor magnetic resonance images. This is less of a problem in structural MRI, because this bias is signal dependent and it does not seriously impair tissue identification or clinical diagnoses. However, diffusion imaging is used extensively for quantita...

An algorithm of the color image noise removal algorithm is put forward based on the pixel operations. The idea of the algorithm is to read every pixel in a set order and determine whether the pixel level is consistent with the probability density function of impulse noise or not. If it is similar to noise pixel, the number of impulse noise in a certain mask is counted. If the number is less tha...

In this paper we present a novel structure for removal of impulse noise which is based on a combination of impulse detection and nonlinear ltering. The impulse detector is realized as a neural network which will be shown to possess a very simple structure. This means that, compared to traditional approaches, a signiicant gain in performance can be achieved with considerably smaller complexity. ...

One of the main problem in biomedical data processing like electrocardiography is the separation of the wanted signal from noises caused by power line interference, external electromagnetic fields and random body movements and respiration. Different types of digital filters are used to remove signal components from unwanted frequency ranges. It is difficult to apply filters with fixed coefficie...

In a previous paper, Abma and Claerbout(1994), presented a technique for separating signal and noise. This technique was fairly expensive since it used an inversion routine that required many iterations to get a reasonable result. Generally the process worked well, but occasionally the traces that contained high amplitude noise showed weak signal on the output. The cause of both the high cost a...

In this paper, we present an adaptive-hierarchical filter that can remove the impulse noise while preserving the details in an image. The global image structure, which is estimated from a set of pyramid images, can be used as prior information in order to apply different filters adaptively. The proposed filter outperforms other methods in that it can make use of both local and global informatio...

In this paper, we introduce a new class of filter, the modified spatial median filter (MSMF) for the removal of impulse noise in digital images. The proposed filter is compared with four different filtering algorithms based on their ability to reconstruct noise-affected images. In-order to better appraise the noise cancellation behavior of our filter from the point of view of human perception, ...

In this paper, we present an effective unshrinkage noise removal algorithm to generate smooth geometric models. By introducing the constraints of keeping all triangle barycenters invariant at each smoothing step, the algorithm converts the mesh fairing issue into the minimization of the constrained energy minimization functional, which is then solved efficiently by our iterative method. The exp...

In this paper a novel adaptive filtering scheme for impulsive noise removal in color images is presented. The noise detection algorithm is based on the concept of aggregated distances assigned to the pixels belonging to the filtering window. The value of the difference between the accumulated distance assigned to the central sample and to the pixel with the lowest rank serves as an indicator of...