Search results for " deconvolution"
showing 5 items of 15 documents
Deconvolution by Regularized Matching Pursuit
2014
In this chapter, an efficient method that restores signals from strongly noised blurred discrete data is presented. The method can be characterized as a Regularized Matching Pursuit (RMP), where dictionaries consist of spline wavelet packets. It combines ideas from spline theory, wavelet analysis and greedy algorithms. The main distinction from the conventional matching pursuit is that different dictionaries are used to test the data and to approximate the solution. In addition, oblique projections of data onto dictionary elements are used instead of orthogonal projections, which are used in the conventional Matching Pursuit (MP). The slopes of the projections and the stopping rule for the …
A sensor-data-based denoising framework for hyperspectral images
2015
Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term…
Mathematical Models for Restoration of Baroque Paintings
2006
In this paper we adapt different techniques for image deconvolution, to the actual restoration of works of arts (mainly paintings and sculptures) from the baroque period. We use the special characteristics of these works in order to both restrict the strategies and benefit from those properties. We propose an algorithm which presents good results in the pieces we have worked. Due to the diversity of the period and the amount of artists who made it possible, the algorithms are too general even in this context. This is a first approach to the problem, in which we have assumed very common and shared features for the works of art. The flexibility of the algorithm, and the freedom to choose some…
Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution
2021
The NEXT collaboration: et al.
Spline Algorithms for Deconvolution and Inversion of Heat Equation
2014
In this chapter, we present algorithms based on Tikhonov regularization for solving two related problems: deconvolution and inversion of heat equation. The algorithms, which utilize the SHA technique, provide explicit solutions to the problems in one and two dimensions.