A method based on cepstral deconvolution technique is proposed for measurement of absorption and scattering coefficients of materials. The reverberation room method standardized by International Organization for Standardization (ISO) is taken as the reference for measurements. Several measurements are conducted in a physically scaled reverberation room and results are evaluated by these two met...

We derive interferometric field representations that are valid for diffusive field methods. The method retrieves the reflection response of the earth, as if the domain above the receiver depth level is homogeneous. It is represented as the flux-normalized up going field deconvolved by the down going field. The deconvolution step can be seen as a weighted crosscorrelation step, which is the usua...

We propose and demonstrate a novel method to improve the accuracy of measurements of group delays using the conventional phase-shift technique. In particular, the method allows for accurate reconstruction of the actual group delay when a high modulation frequency is employed to increase the timing resolution. The method is based on postprocessing of the measured data in a deconvolution operatio...

Biomedical images are often degraded during image acquisition. Two very common degradations that occur in many biomedical imaging modalities are blur and noise. Corrupted images are more difficult to interpret by the physician or researcher and so the goal is to restore the original image. Blurring can be mathematically modeled by convolution, and within this model the blur is characterized by ...

Traditionally blind deconvolution makes the assumption that the reflectivity spike series is white. Earlier we dropped that assumption and adopted the assumption that the output spike series is sparse under a hyperbolic penalty function. This approach now here allows us to take a step further and drop the assumption of minimum phase. In this new method (what we called Bidirectional Sparse Decon...

Although confocal microscopes have considerably smaller contribution of out-of-focus light than widefield microscopes, the confocal images can still be enhanced mathematically if the optical and data acquisition effects are accounted for. For that, several deconvolution algorithms have been proposed. As a practical solution, maximum-likelihood algorithms with regularization have been used. Howe...

PURPOSE Deconvolution based on truncated singular value decomposition (SVD deconvolution) is a promising method for measuring cerebral blood flow (CBF) with dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI), but it has proved extremely sensitive to tracer delay. The purpose of this study was to investigate the effect of regional tracer delay on CBF determined by SVD ...

The desire to recover the unknown density when data are contaminated with errors leads to nonparametric deconvolution problems. Optimal global rates of convergence are found under the weighted Lp-loss (1 $ p $ 00). It appears that the optimal rates of convergence are extremely slow for supersmooth error distributions. To overcome the difficulty, we examine how large the noise level can be for d...

This paper addresses the issue of optimal deconvolution density estimation on the 2-sphere. Indeed, by using the transitive group action of the rotation matrices on the 2-dimensional unit sphere, rotational errors can be introduced analogous to the Euclidean case. The resulting density turns out to be convolution in the Lie group sense and so the statistical problem is to recover the true under...

Approximate deconvolution forms a mathematical framework for the structural modeling of turbulence. The sub-filter scale flow quantities are typically recovered by using the Van Cittert iterative procedure. In this paper, however, we put forth a generalized approach for the iterative deconvolution process of sub-filter scale recovery of turbulent flows by introducing Krylov space iterative meth...