Displaying similar documents to “Adaptive image enhancement algorithm combining kernel regression and local homogeneity.”

Application of the adaptive center-weighted vector median framework for the enhancement of cDNA microarray images

Rastislav Lukac, Bogdan Smołka (2003)

International Journal of Applied Mathematics and Computer Science

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In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing the sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of the so called gene chips....

Nonlinear image processing and filtering: A unified approach based on vertically weighted regression

Ewaryst Rafajłowicz, Mirosław Pawlak, Angsar Steland (2008)

International Journal of Applied Mathematics and Computer Science

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A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach is a nonlinearly modified version of the classical nonparametric regression estimates utilizing the concept of vertical weighting. The method unifies a number of known nonlinear image filtering and denoising algorithms such as bilateral and steering kernel filters. It is shown that vertically weighted filters can be realized by...

On the optimality of a new class of 2D recursive filters

Leopoldo Jetto (1999)

Kybernetika

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The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures...

Image retrieval based on hierarchical Gabor filters

Tomasz Andrysiak, Michal Choraś (2005)

International Journal of Applied Mathematics and Computer Science

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Content Based Image Retrieval (CBIR) is now a widely investigated issue that aims at allowing users of multimedia information systems to automatically retrieve images coherent with a sample image. A way to achieve this goal is the computation of image features such as the color, texture, shape, and position of objects within images, and the use of those features as query terms. We propose to use Gabor filtration properties in order to find such appropriate features. The article presents...

A simultaneous localization and tracking method for a worm tracking system

Mateusz Kowalski, Piotr Kaczmarek, Rafał Kabaciński, Mieszko Matuszczak, Kamil Tranbowicz, Robert Sobkowiak (2014)

International Journal of Applied Mathematics and Computer Science

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The idea of worm tracking refers to the path analysis of Caenorhabditis elegans nematodes and is an important tool in neurobiology which helps to describe their behavior. Knowledge about nematode behavior can be applied as a model to study the physiological addiction process or other nervous system processes in animals and humans. Tracking is performed by using a special manipulator positioning a microscope with a camera over a dish with an observed individual. In the paper, the accuracy...