This paper discusses blind identification and deconvolution of two-input two-output channels corrupted by noises based on secondorder statistics. First, the identifiability of channel is analyzed. By constructing an new criterion, the channel parameters can be identified precisely in the present of noises. Second, the cost function of identification is established and the corresponding algorith...

We present an approach to determine sufficient conditions for the global convergence of iterative blind deconvolution algorithms using finite impulse response (FIR) deconvolution filters. The novel technique, which incorporates Lyapunov’s direct method, is general, flexible, and can be easily adapted to analyze the behavior of many types of nonlinear iterative signal processing algorithms. Spec...

In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deco...

This paper introduces a novel blind on-line dereverberation algorithm for speech signals based on a natural gradient deconvolution algorithm. Existing blind dereverberation algorithms often employ a structure that performs speech prewhitening using LPC analysis followed by a blind deconvolution step applied to the LPC residual. Here it is shown that better performance can be achieved by respect...

This paper describes a technique for the blind deconvolution of extended objects such as Hubble Space Telescope ( H S T ) , scanning electron and 3D fluorescence microscope images. T h e blind deconvolution mechanism i s based o n the Richardson-Lucy algorithm and alternates between deconvolution of the image and point spread func t ion ( P S F ) . This f o r m of iterative blind deconvolution ...

Three-dimensional microscopy by computational deconvolution methods requires accurate knowledge of the point spread function (PSF) that characterizes the microscope. Experimental PSF’s can only be measured over small regions about focus because the small objects necessary for PSF measurement are dim. Theoretical computation of the PSF requires accurate knowledge of all the experimental setup pa...

Starting from maximizing information ow through a nonlinear neuron Bell and Sejnowski derived adaptation equations for blind deconvolution using an FIR lter [1]. In this paper we will derive a simpler form of the adaptation and we will apply it to more complex lter structures, such as recursive lters. As an application, we study blind echo cancellation for speech signals. We will also present a...

The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences and a priori Laplacian distribution for deconvolved signal. The algorithm is executed in two steps. Firstly,...

Image Restoration is a field of Image Processing which deals with recovering an original and sharp image from a degraded image using a mathematical degradation and restoration model. This study focuses on restoration of degraded images which have been blurred by known or unknown degradation function. On the basis of knowledge of degradation function image restoration techniques can be divided i...