The deconvolution kernel density estimator is a popular technique for solving the deconvolution problem, where the goal is to estimate a density from a sample of contaminated observations. Although this estimator is optimal, it suffers from two major drawbacks: it converges at very slow rates (inherent to the deconvolution problem) and can only be calculated when the density of the errors is co...

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to g...

Introduction Several deconvolution methods have been proposed to increase the angular resolution of HARDI or QBI [1][2]. However, there is no deconvolution method directly applied to diffusion ODF without resorting to spherical decomposition. In this study, we developed a deconvolution method that could be directly applied to diffusion ODF, thus extending its applicability to other q-space meth...

In guided wave pipeline inspection, echoes reflected from closely spaced reflectors generally overlap, meaning useful information is lost. To solve the overlapping problem, sparse deconvolution methods have been developed in the past decade. However, conventional sparse deconvolution methods have limitations in handling guided wave signals, because the input signal is directly used as the proto...

Under certain conditions, multi-frame image sequences can be processed to produce images that achieve greater resolution through image registration and increased sampling. This technique, known as super-sampling, takes advantage of the spatial-temporal data available in an under-sampled imaging sequence. In this effort, the image registration is replaced by application of a fast blind deconvolu...

Myopic deconvolution from wave front sensing (MDWFS) is a powerful tool for high-resolution imaging. It is typically used with monochromatic, short exposure images with integration times less than the coherence time for the atmosphere, and Shack-Hartmann wave-front sensor data where the number of sub-apertures across the pupil is commensurate with the turbulence strength D/r0 where D is the dia...

Controlled Source Electromagnetic (CSEM) is an important technique in hydrocarbon exploration, because it uses the large contrast in electrical resistivity to distinguishes between water and hydrocarbons. In a shallow sea environment, the airwave that is refracted from the air-water interface dominates the recorded signal at large offsets. Therefore, the hydrocarbon detection ability of the CSE...