annihilation or reduction of each kind of noise blended in correct data signals is a field that has attracted many researchers. it is a fact that fuzzy theory presents full capability in this field. fuzzy filters are often strong in smoothing corrupted signals, whereas they have simple structures. in this paper, a new powerful yet simple fuzzy procedure is introduced for sharpness reduction in ...

Smoothness priors and quadratic variation (QV) regularization are widely used techniques in many applications ranging from signal image processing, computer vision, pattern recognition, other fields of engineering science. In this contribution, an extension such algorithms to band-stop smoothing filters (BSSFs) is investigated. For designing a BSSF, the most important parameters order cutoff fr...

To alleviate excessive smoothing of high signal-to-noise ratio (SNR) regions which are correspond to the structural features of MR images by using classical anisotropic diffusion (AD) filter. A novel AD filter called SNR controlled anisotropic diffusion is proposed. In this filter, an adaptive diffusivity function which is based on the correction factor of MR images was constructed. This adapti...

For mapping or object identification, the edges possess important information. It would be desirable to preserve the edges in the original image, while applying smoothing filter to reduce the influence of noise. A number of filters are available for this purpose, including the Mean Filter, Median Filter, Kuwahara Filter, and Symmetric Nearest Neighbor Filter (SNNF). This study investigates the ...

In this paper, we combine the well-established technique of Wiener filtering with an efficient method for robust smoothing: channel smoothing. The main parameters to choose in channel smoothing are the number of channels and the averaging filter. Whereas the number of channels has a natural lower bound given by the noise level and should for the sake of speed be as small as possible, the averag...

Digital image processing heavily relies on the connectivity of pixels, as it is a vital component for accurate object identification and analysis within an image. Grouping together pixels with similar features such colour intensity, allows formation meaningful patterns or objects, which essential recognition segmentation. This approach particularly valuable in photogrammetric imaging, video sur...

The canny edge detection technique is a multi-stage algorithm which is an optimal edge detection technique. But it removes noise in an image using Gaussian filter to become insensitive to noise. The Gaussian filter smoothes even the edges in the images so that the through put is decreased. That is some of the true edges may be missed and false edges may appear in the edge detection. We propose ...

The multi-point values of an appropriate smoothing parameter of HP-filter algorithm for midterm electricity load demand (MELD) forecasting are proposed. The case study employs the data based on the organization of the Electricity Generating Authority of Thailand (EGAT). The research shows the growth at rate of weather and economic factors influencing to the electricity demand. The main focus of...

Recently, significant progress has been made developing kernel mean expressions for Bayesian inference. An important success in this domain is the nonparametric kernel Bayes’ filter (nKB-filter), which can be used for sequential inference in state space models. We expand upon this work by introducing a smoothing algorithm, the nonparametric kernel Bayes’ smoother (nKB-smoother) which relies on ...

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...