Smoothing or filtering of data is first preprocessing step for noise suppression in many applications involving data analysis. Moving average is the most popular method of smoothing the data, generalization of this led to the development of Savitzky-Golay filter. Many window smoothing methods were developed by convolving the data with different window functions for different applications; most ...

Image is a multimedia component rich in information and has an essential role as provider. However, the images encountered often experience decrease quality, such defects or noise, causing conveyed from these less clear. Noise causes image to be too contrasted, blurry, not sharp enough. One type of noise contrast noise. Smoothing here one operations improve quality which aims smooth out with un...

In Image processing, image decomposition and restoration for blurred images are the significant challenges. Using bilateral filter, image is decomposed into two meaningful components. One is the cartoon component which is often called as geometrical part or sketchy approximation. Other is the texture component which is often called as oscillating part or small scale special pattern. Image resto...

Spatial filters have been used as an easy and intuitive way to create smoothed disease maps. Birth weight data from New York State for 1994 and 1995 are used to compare the traditional filter type of fixed geographical size with a filter size of constant or nearly constant population size. The latter are more appropriate for mapping disease in geographic areas with widely varying population den...

This paper presents the study of 2D Gaussian filter and its vitality in image processing domain. The smoothing of images using 2D Gaussian filter brings out the best outcomes as compared to the conventional filters used to the date. Furthermore, when it comes to real time implementation of filter used for the image processing; it becomes a quite daunting task for the designers as it requires hi...

In this paper, we present a method for edge segmentation of satellite images based on 2-D Phase Congruency (PC) model. The proposed approach is composed by two steps: The contextual non linear smoothing algorithm (CNLS) is used to smooth the input images. Then, the 2D stretched Gabor filter (S-G filter) based on proposed angular variation is developed in order to avoid the multiple responses in...

The Savitzky–Golay smoothing and differentiation filter optimally fits a set of data points to a polynomial in the least-squares sense. The Savitzky–Golay filter has been developed and generalized well in the literatures. However, the data subset is subject to an odd number ð2m þ 1Þ: In this communication, the Savitzky–Golay filter is extended for even number data. Simulations are performed to ...

Remote sensing image dehazing is challenging because it is massively ill-posed and the haze is dependent on the unknown depth information. Haze removal based on dark channel prior is effective, and refining the transmission map with Gaussian filter will produce a god result. But need to improve the naturalness and sharpness and effectiveness of images and to remove fine haze . So Proposes new a...

This paper provides a detailed analysis of how anisotropic diffusion filters work on seismic data. The conventional trace mixing filter is shown to be an implementation of a specific d i ffusion process. Diffusion filters have diff e rent forms, ranging from the simplest linear isotropic (L-I) diffusion to the most complex nonlinear anisotropic (NL-AI) diffusion. The NL-AI diffusion filter can ...

Due to the significant amount of noise in Sea Surface Temperature (SST) images that originate from different atmospheric sources and the sensor itself, current detection methods detect false fronts or neglect to detect fronts. Various methods have been used to filter the SST images including low-pass filter [1], contextual filter [2], adaptive filtering [3] and others [4]. The present paper int...