Although spatial deblurring is relatively well understood by assuming that the blur kernel is shift invariant, motion blur is not so when we attempt to deconvolve on a frame-by-frame basis: this is because, in general, videos include complex, multilayer transitions. Indeed, we face an exceedingly difficult problem in motion deblurring of a single frame when the scene contains motion occlusions....

This paper tries to understand the study of Restored Motion Blurred Images by using four types of deblurring methods: Regularized filter, Wiener filter, Lucy Richardson and Blind Image Deconvolution. There are some indirect restoration techniques like Regularized filtering, Weiner filtering, LR Filtering in which restoration results are obtained after number of iterations. The problem of such m...

We present an effective method for defocus map estimation from a single natural image. It is inspired by the observation that defocusing can significantly affect the spectrum amplitude at the object edge locations in an image. By establishing the relationship between the amount of spatially varying defocus blur and spectrum contrast at edge locations, we first estimate the blur amount at these ...

We derive moment inequalities for the supremum of empirical processes of U-Statistic structure and give application to kernel type density  estimation ‎and estimation of the distribution function for functions of observations.  

In this paper, a no reference blur image quality metric based on wavelet transform is presented. As blur affects specially edges and image fine details, most blur estimation algorithms, are based primarily on an adequate edge detection methods. Here we propose a new approach by analyzing edges through a multi-resolution decomposition. The ability of wavelets to extract the high frequency compon...

In pattern recognition problems, the effectiveness of the analysis depends heavily on the quality of the image to be processed. This image may be blurred and/or noisy and the goal of digital image restoration is to find an estimate of the original image. A fundamental issue in this process is the blur estimation. When the blur is not readily avalaible, it has to be estimated from the observed i...

in this paper at first , we discuss about nonlinear pseudoparabolic equations with nonlocalboundary conditions and their results.at second we use an effective error estimation for this method altough has not yet beendiscussed. the aim of this paper is to fill this gap.

In this paper, we propose a new measure for estimating defocus blur in document images and compare it with a good existing method proposed in [1]. This new measure is the average value of blur levels of edge points detected by the method proposed in [2]. This method uses three edge models (transition, peak and line) and analytically calculates their maxima functions. Then maxima functions of th...