The attenuated ultrasound pulse is divided into two parts: a stationary basic pulse and a nonstationary attenuation pulse. A standard ARMA model is used for the basic pulse, and a nonstandard ARMA model is derived for the attenuation pulse. The maximum likelihood estimator of the attenuated ultrasound pulse, which includes a maximum likelihood attenuation estimator, is derived. The results of t...

Reflection coefficients are observed in nature to have stochastic behavior that departs significantly from the white noise model. Conventional deconvolution methods, however, assume reflectivity to be a white noise process. In this paper we analyze the deconvolution process, study the implications of the assumption of white noise, and show that the conventional operator can recover only the whi...

Camera shake during exposure leads to image blur and poses an important problem in digital photography. Blind deconvolution recovers the sharp original image from a blurred image. MAP has been the most widely used deconvolution field but naive MAP methods mostly tends to favour no-blur solution. An intermediate representation of the image called unnatural representation has been found to the ma...

Joint estimation of direction of arrival (DOA) and time delay plays a great role in source localization, which attracts many researchers not only in the areas of radar, sonar, geological exploration but also in wireless communication. [1][2][3][4] M. Wax applies approximate MLE with iteration algorithm , which convert a 2-D search into two or three 1-D search. A.J.van der Veen use 2-D ESPRIT to...

Image restoration is the process of recovering the original image from the degraded or noisy image. We are using multiple images for processing, the identifier select the blur image for further process and restore after applying the algorithms. Our object is identifying the blur image and restores them by parallel distributed computing. We are using blind deconvolution algorithm for restoration...

The past decade has seen rapid growth in the use of diverse compound libraries in classical phenotypic screens to identify modulators of a given process. The subsequent process of identifying the molecular targets of active hits, also called 'target deconvolution', is an essential step for understanding compound mechanism of action and for using the identified hits as tools for further dissecti...

We report on the initial results obtained with an image convolution/deconvolution computer code that we developed and used to study formation capabilities of solar gravitational lens (SGL). Although SGL a spherical Sun creates greatly blurred image, knowledge SGL's point-spread function (PSF) makes it possible reconstruct original remove blur by way deconvolution. discuss deconvolution process,...

keywords Input reconstruction, deconvolution, holomorphic semigroups Reconstruction of input signals to linear dynamical systems is an important problem. In fact, in the time invariant case, it is a special instance of the deconvolution problem. Several algorithms have been proposed to achieve this goal, which can be classified in two large classes: off-line and on-line deconvolution algorithms...

Deconvolution techniques have long been used for image reconstruction, and because it works particularly well on sparse images, it has recently been applied successfully in stochastic optical reconstruction microscopy (STORM) [1,2]. While having the advantage of using genetically encoded probes (applicable in live-cell imaging) photoactivated localization microscopy PALM [3] however, presents d...