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From the Slit-Island Method to the Ising model: Analysis of irregular grayscale objects

Przemysław Mazurek, Dorota Oszutowska-Mazurek (2014)

International Journal of Applied Mathematics and Computer Science

The Slit Island Method (SIM) is a technique for the estimation of the fractal dimension of an object by determining the area-perimeter relations for successive slits. The SIM could be applied for image analysis of irregular grayscale objects and their classification using the fractal dimension. It is known that this technique is not functional in some cases. It is emphasized in this paper that for specific objects a negative or an infinite fractal dimension could be obtained. The transformation...

Fusion based analysis of ophthalmologic image data

Jiří Jan, Radim Kolář, Libor Kubečka, Jan Odstrčilík, Jiří Gazárek (2011)

Kybernetika

The paper presents an overview of image analysis activities of the Brno DAR group in the medical application area of retinal imaging. Particularly, illumination correction and SNR enhancement by registered averaging as preprocessing steps are briefly described; further mono- and multimodal registration methods developed for specific types of ophthalmological images, and methods for segmentation of optical disc, retinal vessel tree and autofluorescence areas are presented. Finally, the designed methods...

Fuzzy morphological operators in image processing.

Pedro J. Burillo López, Noé Frago Paños, Ramón Fuentes González (2003)

Mathware and Soft Computing

First of all, in this paper we propose a family of fuzzy implication operators, which the generalised Lukasiewicz's one, and to analyse the impacts of Smets and Magrez properties on these operators. The result of this approach will be a characterisation of a proposed family of inclusion grade operators (in Bandler and Kohout's manner) that satisfies the axioms of Divyendu and Dogherty. Second, we propose a method to define fuzzy morphological operators (erosions and dilations). A family of fuzzy...

Fuzzy sets in computer vision: an overview.

Pilar Sobrevilla, Eduard Montseny (2003)

Mathware and Soft Computing

Every computer vision level crawl with uncertainty, what makes its management a significant problem to be considered and solved when trying for automated systems for scene analysis and interpretation. This is why fuzzy set theory and fuzzy logic is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision.The growth within the use of fuzzy set theory in computer vision is keeping pace with the use of more complex algorithms addressed to solve...

Fuzzy transforms in image compression and fusion

Irina Perfilieva (2007)

Acta Mathematica Universitatis Ostraviensis

An overview of direct and inverse fuzzy transforms of three types is given and applications to data processing are considered. The construction and some important properties of fuzzy transforms are presented on the theoretical level. Three applications of F -transform to data processing have been chosen: compressional and reconstruction of data, removing noise and data fusion. All of them successively exploit the filtering property of the inverse fuzzy transform.

Generation of fuzzy mathematical morphologies.

Pedro J. Burillo López, Noé Frago Paños, Ramón Fuentes González (2001)

Mathware and Soft Computing

Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations fuzzy erosion, dilation, opening and closing, we introduce a general method based upon fuzzy implication and inclusion grade operators, including as particular case, other ones existing in related literature. In the definition of fuzzy erosion and dilation we use several fuzzy implications (Annexe A, Table of fuzzy implications), the paper includes...

Gradient flow optimization for reducing blocking effects of transform coding

Feng Gao, Xiaokun Li, Xun Wang, William Wee (2004)

International Journal of Applied Mathematics and Computer Science

This paper addresses the problem of reducing blocking effects in transform coding. A novel optimization approach using the gradient flow is proposed. Using some properties of the gradient flow on a manifold, an optimized filter design method for reducing the blocking effects is presented. Based on this method, an image reconstruction algorithm is derived. The algorithm maintains the fidelity of images while reducing the blocking effects. Experimental tests demonstrate that the presented algorithm...

Image Compression with Schauder Bases

Zbigniew Ciesielski (2001)

Applicationes Mathematicae

As is known, color images are represented as multiple, channels, i.e. integer-valued functions on a discrete rectangle, corresponding to pixels on the screen. Thus, image compression, can be reduced to investigating suitable properties of such, functions. Each channel is compressed independently. We are, representing each such function by means of multi-dimensional, Haar and diamond bases so that the functions can be remembered, by their basis coefficients without loss of information. For, each...

Image deblurring, spectrum interpolation and application to satellite imaging

Sylvain Durand, François Malgouyres, Bernard Rougé (2010)

ESAIM: Control, Optimisation and Calculus of Variations

This paper deals with two complementary methods in noisy image deblurring: a nonlinear shrinkage of wavelet-packets coefficients called FCNR and Rudin-Osher-Fatemi's variational method. The FCNR has for objective to obtain a restored image with a white noise. It will prove to be very efficient to restore an image after an invertible blur but limited in the opposite situation. Whereas the Total Variation based method, with its ability to reconstruct the lost frequencies by interpolation, is very...

Image processing for old movies by filters with motion detection

Sławomir Skoneczny (2005)

International Journal of Applied Mathematics and Computer Science

Old movies suffer from various types of degradation: severe noise, blurred edges of objects (low contrast), scratches, spots, etc. Finding an efficient denoising method is one of the most important and one of the oldest problems in image sequence processing. The crucial thing in image sequences is motion. If the motion is insignificant, then any motion noncompensated method of filtering can be applied. However, if the noise is significant, then this approach gives most often unsatisfactory results....

Image recall using a large scale generalized Brain-State-in-a-Box neural network

Cheolhwan Oh, Stanisław Żak (2005)

International Journal of Applied Mathematics and Computer Science

An image recall system using a large scale associative memory employing the generalized Brain-State-in-a-Box (gBSB) neural network model is proposed. The gBSB neural network can store binary vectors as stable equilibrium points. This property is used to store images in the gBSB memory. When a noisy image is presented as an input to the gBSB network, the gBSB net processes it to filter out the noise. The overlapping decomposition method is utilized to efficiently process images using their binary...

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