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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...

Image segmentation with a finite element method

Blaise Bourdin (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

The Mumford-Shah functional for image segmentation is an original approach of the image segmentation problem, based on a minimal energy criterion. Its minimization can be seen as a free discontinuity problem and is based on Γ-convergence and bounded variation functions theories. Some new regularization results, make possible to imagine a finite element resolution method. In a first time, the Mumford-Shah functional is introduced and some existing results are quoted. Then, a discrete formulation...

Implementing Dynamic Visualization as an Alternative Interface to a Digital Mathematics Library

Nevěřilová, Zuzana (2010)

Towards a Digital Mathematics Library. Paris, France, July 7-8th, 2010

This paper presents an alternative interface for browsing in the Czech Digital Mathematics Library (DML-CZ) using our Visual Browser web browsing tool. Using dynamic visualization, we have created a tool for browsing the library graphically. Visualization can help users orient themselves in complex data and at the same time reveal sometimes unexpected relationships among units; it at least speeds up browsing. This work follows the metadata processing undertaken on DML-CZ and visualizes all reasonable...

Impulse noise removal based on new hybrid conjugate gradient approach

Morteza Kimiaei, Majid Rostami (2016)

Kybernetika

Image denoising is a fundamental problem in image processing operations. In this paper, we present a two-phase scheme for the impulse noise removal. In the first phase, noise candidates are identified by the adaptive median filter (AMF) for salt-and-pepper noise. In the second phase, a new hybrid conjugate gradient method is used to minimize an edge-preserving regularization functional. The second phase of our algorithm inherits advantages of both Dai-Yuan (DY) and Hager-Zhang (HZ) conjugate gradient...

Innovative applications of associative morphological memories for image processing and pattern recognition.

Manuel Graña, Peter Sussner, Gerhard Ritter (2003)

Mathware and Soft Computing

Morphological Associative Memories have been proposed for some image denoising applications. They can be applied to other less restricted domains, like image retrieval and hyperspectral image unsupervised segmentation. In this paper we present these applications. In both cases the key idea is that Autoassociative Morphological Memories selective sensitivity to erosive and dilative noise can be applied to detect the morphological independence between patterns. Linear unmixing based on the sets of...

INSPIRE: Realizing the Dream of a Global Digital Library in High-Energy Physics

Holtkamp, Annette, Mele, Salvatore, Šimko, Tibor, Smith, Tim (2010)

Towards a Digital Mathematics Library. Paris, France, July 7-8th, 2010

High-Energy Physics (HEP) has a long tradition in pioneering infrastructures for scholarly communication, and four leading laboratories are now rolling-out the next-generation digital library for the field: INSPIRE. This is an evolution of the extraordinarily successful, 40-years old SPIRES database. Based on the Invenio software, INSPIRE already provides seamless access to almost 1 million records, which will be expanded to cover multimedia, data, software, wikis. Services offered include citation...

Instability of the eikonal equation and shape from shading

Ian Barnes, Kewei Zhang (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

In the shape from shading problem of computer vision one attempts to recover the three-dimensional shape of an object or landscape from the shading on a single image. Under the assumptions that the surface is dusty, distant, and illuminated only from above, the problem reduces to that of solving the eikonal equation |Du|=f on a domain in ℝ 2 . Despite various existence and uniqueness theorems for smooth solutions, we show that this problem is unstable, which is catastrophic for general numerical algorithms. ...

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