Analysis and interpretation of an image which was acquired by a nonideal imaging system is the key problem in many application areas. The observed image is usually corrupted by blurring, spatial degradations, and random noise. Classical methods like blind deconvolution try to estimate the blur parameters and to restore the image. In this paper, we propose an alternative approach. We derive the ...

Blind image restoration is a non-convex problem which involves restoration of images from an unknown blur kernel. The factors affecting the performance of this restoration are how much prior information about an image and a blur kernel are provided and what algorithm is used to perform the restoration task. Prior information on images is often employed to restore the sharpness of the edges of a...

In constructing the percept of transparency, the visual system must decompose the light intensity at each image location into two components one for the partially transmissivc surface, the other for the underlying surface seen through it. Theories of perceptual transparency have typically assumed that this decomposition is defined quantitatively in terms of the inverse of some physical model (t...

Abstract— Image, audio and video are the popular entertainment and communication services of internet. Sometime they suffer from many problems, Blur is one of them. Blur is a factor that breakdown the status of image. In this paper, we are going to perform comparison of four different Blur Detection classifiers. This paper introduces our proposed technique (Hybrid Classifier). To verify the acc...

The last two decades brought significant progress in the development of efficient methods for classical deconvolution and super-resolution problems in both the single and multi-image scenarios. Most of these methods work with blurs modelled by convolution, which assumes that the properties of blur are the same 2 Image Restoration: Fundamentals and Recent Advances in the whole image (space-invar...

We deal with the problem of restoration of images blurred by relative motion between the camera and the object of interest. This problem is common when the imaging system is in moving vehicles or held by human hands, and in robot vision. For correct restoration of the degraded image, it is useful to know the point-spread function (PSF) of the blurring system. We propose a straightforward method...

of the Dissertation Investigation of a Localized Approach to Shift-Variant Image Restoration and Robust Autofocusing by Younsik Kang Doctor of Philosophy in Electrical Engineering Stony Brook University 2011 Images of three-dimensional (3D) scenes or dynamic scenes captured by a digital camera are in general blurred by different degrees at different points in the image. The blur level at a pixe...