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...

This study suggests a fuzzy anisotropic smoothing technique on scalar (grayscale) images using partial differential equations (PDEs) and fuzzy sets. This technique preserves the image details such as edges while noise is being reduced. The PDE and fuzzy rule based techniques are employed in approximation of smoothing coefficients calculated based on structure and noisiness information. Utilizin...

in this note, we introduce the concept of a fuzzy filter of a blalgebra,with respect to a t-norm briefly, t-fuzzy filters, and give some relatedresults. in particular, we prove representation theorem in bl-algebras. thenwe generalize the notion of a fuzzy congruence (in a bl-algebra) was definedby lianzhen et al. to a new fuzzy congruence, specially with respect to a tnorm.we prove that there i...

We consider the fuzzification of the notion of a positive implicative ordered filter in implicative semigroups. We show that every fuzzy positive implicative ordered filter is both a fuzzy ordered filter and a fuzzy implicative ordered filter. We give examples that a fuzzy (implicative) ordered filter may not be a fuzzy positive implicative ordered filter. We also state equivalent conditions of...

A modification of the neo-fuzzy neuron is proposed (an extended neo-fuzzy neuron (ENFN)) that is characterized by improved approximating properties. An adaptive learning algorithm is proposed that has both tracking and smoothing properties and solves prediction, filtering and smoothing tasks of non-stationary “noisy” stochastic and chaotic signals. An ENFN distinctive feature is its computation...

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...

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the Lagrangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the crossvalidation procedure for selecting the o...

Fuzzy semigroup theory concentrates on theoretical aspects, but also includes applications in the areas of fuzzy coding theory, fuzzy finite state machines, and fuzzy languages. In this paper, we introduce the concept of an ( , )-fuzzy filter of an ordered semigroup , where , , , , with . Since the concept of ( , )-fuzzy filter is an important and useful generalization of ordinary fuzzy filter,...

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 ...