In this paper, we proposed a new adaptive median filter for image denoising. In our method, two thresholds have been involved for detecting noises in variable-sized windows. The median filter and the mean filter are combined for changing the value of the corrupted pixels. The filter can preserve the fine details of image while suppressing the impulsive-type noise. The results of the experiments...

It is universally accepted that Median filter is the best filter known so far. Based on this fact many variants of median filter were developed to improve the performance of the standard median filter. In this paper a new approach for the restoration of gray scale and color images that are highly corrupted by impulse noise is proposed. The algorithm works on low density noise also. The algorith...

Median filter is well known for removing impulsive noise and preserving edges. Repeatedly filtering of any one-dimensional signal with a median filter will produce a root signal. Any impulses in the input signal will be removed by sufficient number of passes of median filter, where any root like features in the input signal will be preserved. A signal of finite length will be filtered to a root...

The median filter is a special case of nonlinear filter used for smoothing signals. Since the output of the median filter is always one of the input samples, it is conceivable that certain signals could pass through the median filter unaltered. These signals, invariant to further passes of the median filter, define the signature of a filter and are referred to as root signals. This represents t...

Abstract: In this paper, image-denoising proposed median filter is implemented for denoising of corrupted image and edge preservation. This method enhances the Peak Signal to Noise Ratio(PSNR) and perceives the original features of the images. This filter is compared with median and Adaptive median filter. The paper is organized as follows. Section II presents the introduction to image processi...

This paper presents digital image stabilization with sub-image phase correlation based global motion estimation and Kalman filtering based motion correction. Global motion is estimated from the local motions of four subimages each of which is detected using phase correlation based motion estimation. The global motion vector is decided according to the peak values of sub-image phase correlation ...

In this paper, we present a spatially adaptive filter for color median filtering. Several alternative implementations of such a filter are given, using different ways of gradient computation. Then, several methods of color median filtering are compared in terms of performance on a particular image. Vector median filters are considered as well as median filters inspired by grey-

Finger vein is a unique physiological biometric for identifying individuals based on the physical characteristics and attributes of the vein patterns in the human. The technology is currently in use or development for a wide variety of applications, including credit card authentication, automobile security, employee time and attendance tracking, computer and network authentication, end point se...

Image filtering is a essential part of image processing. There are various filter are available but gives better result only for particular noise. Median filter are one of them median filter give better result for 'salt and pepper' noise but when we use this filter in Gaussian noise not give better result. We are proposing a new median filter with some modification of existing median ...

DWM (Directional weighted median) filter is very popular in filtering digital image and remove mixed noise. Fuzzy logic implemented with median filters to improve its performance. In the previous work, fuzzy system switching gives better performance than directional as well filter. Experimenting same didn’t yield results therefore parameters has been changes per strong points of a constant incl...