Performances of iterative blind deconvolution methods for motion-blurred images are usually reduced depending on the accuracy of the required initial guess of the blur. We examine this dependency, and a two-stage restoration procedure is proposed: First we perform a direct technique with a single straight-forward process to produce a rough initial estimate of the blur, and then an iterative tec...

introduction: renal dynamic study is a well-established and popular test in routine practice of nuclear medicine. the test is non-invasive, rapid and unique in evaluation of the kidney function. in despite of its clinical values, the parameters derived from renogram are physiologically meaningless. that is due to the fact that renogram is not the true kidney function. from mathematical points o...

1 Analyzing General Properties of Network Deconvolution 3 1.1 Network deconvolution algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Optimality analysis of network deconvolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Modeling assumptions and intuitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

Source-filter models are widely used in numerous audio processing fields, from speech processing to percussive/contact sound synthesis. The design of filters for these models—be it from scratch or from spectral analysis—usually involves tuning frequency and damping parameters and/or providing an all-pole model of the resonant part of the filter. In this context, and for the modelling of percuss...

In conventional Compton camera systems, the image reconstruction is performed only in two-dimensional or three-dimensional spatial coordinates for a specific gamma-ray energy. By doing so, a priori knowledge of the incident gamma-ray energy is required, and usually an energy window is applied to select full energy deposition events. In some other applications, spectral-deconvolution algorithms ...

Newly emerged probabilistic image patch priors, such as Expected Patch Log-Likelihood (EPLL), have shown excellent performance on image restoration tasks, especially deconvolution, due to its rich expressiveness. However, its applicability is limited by the heavy computation involved in the associated optimization process. Inspired by the recent advances on using regression trees to index prior...

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We present a new method for general multidimensional multichannel deconvolution with finite impulse response (FIR) convolution and deconvolution filters using Gröbner bases. Previous work formulates the problem of multichannel FIR deconvolution as the construction of a left inverse of the convolution matrix, which is solved by numerical linear algebra. However, this approach requires the prior ...

DECONVOLUTION ALGORITHMS FOR FLUORESCENCE AND ELECTRONMICROSCOPY bySiddharth Shah Chair: Andrew E. Yagle In many imaging applications the image formation process is influenced by thedevice physics of the imaging system. As a result, the image is a distorted version ofthe object. This distortion effect, mathematically modeled as the transfer function,ultimately limits the res...

Image deconvolution continues to be an active research topic of recovering a sharp image, given a blurry one generated by a convolution. One of the most challenging problems in image deconvolution is how to preserve the fine scale texture structures while removing blur and noise. Various methods have been proposed in both spatial and transform domains, such as gradient based methods, nonlocal s...