Identical Dual Lattices and Subdivision of Space
Image Compression with Schauder Bases
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
Image deblurring, spectrum interpolation and application to satellite imaging
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 dithering based on the wavelet transform.
Image location for screw dislocation. A new point of view.
Image pre-processing tool
Image processing for old movies by filters with motion detection
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
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 restoration through subimages and confidence images.
Image sampling with quasicrystals.
Image segmentation using gray-scale morphology and marker-controlled watershed transformation.
Image segmentation with a finite element method
Image segmentation with a finite element method
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
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...
Implicitly Representing Arrangements of Lines or Segments.
Improved Bounds on Weak e-Nets for Convex Sets.
Improved free-form modelling of scattered data by dynamic neural networks.
Impulse noise removal based on new hybrid conjugate gradient approach
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...
Independent and identically distributed pseudo-random samples