In image deconvolution or restoration using Kalman filter, the image and blur models are required to be known for the restoration process. Generally, the accuracy of the restoration depends on the accuracy of the given models. Unfortunately, the image and blur models are normally unknown in practice. To solve the problem, an identification stage is employed to estimate the image and blur models...

Inpainting and denoising are two important tasks in the field of image processing with broad applications in image and vision analysis. In this paper, we present a new approach for image restoration. Our method simultaneously fills in missing, corrupted, or undesirable information while it removes noise. The denoising is performed by the smoothing equation working inside and outside of the inpa...

The Geman and Geman image restoration algorithm has been shown to be eeective on reducing noise in single binary images. This project investigates how the algorithm can be extended to reduce noise on moving binary images.

Digital images suffer blurring from various known and unknown point spread functions. Image restoration from degraded image is very big problem in image processing. Image restoration is a process by which a noisy or degraded image is converted into nearly an original image. Improvement in the appearance of the image is done by image restoration. In this paper a Memetic Algorithm is used to rest...

In this paper, we propose the use of complexity reg-ularization in image restoration. This is a exible estimation method which borrows from recent developments in nonparametric estimation theory. The regu-larized estimation problem is formulated in the wavelet domain and solved using a computationally eecient multiscale relaxation algorithm.

The design and analysis of an algorithm for the restoration of degraded images of machine-printed characters is presented. The input is a set of degraded bilevel images of a single unknown character ; the output is an approximation to the charac-ter's ideal artwork. The algorithm seeks to minimize the discrepancy between the approximation and the ideal, measured as the worst-case Euclidean dist...

Two local adaptative nonlinear lters for image denoising are described and compared to other methods. The rst one is a median lter computed over a connected neighborhood that ts the local conformation of level lines. The second one deals with the size of grains in image. Both lters depend on a single parameter, the area A, are morphological and associated with smooth as well as unsmooth xed poi...

A new model adaptive method is proposed for restoration of blurred and noise corrupted images. This approach exploits information available from observed data to choose the appropriate optimization criterion and produce an approximate maximum likelihood solution. The generalized p-Gaussian family of probability distributions is used to model a wide range of observed noise classes. Distribution ...

Image restoration is used to repair solar images degraded by the turbulence in Earth’s atmosphere. Restoration algorithms are based on models of the optical system that produce the images – from the solar source of radiation, through Earth’s atmosphere and telescope/instrument optics, to the detectors recording the data. In this review, these model components are discussed in the context of two...

A. Murat Tekalp Koç University 15.