Iterative Identification and Restoration of Images







ITERATIVE IDENTIFICATION AND RESTORATION OF IMAGES
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ABSTRACT In order to restore distorted images, the unknown blurs have to be identified from the blurred images themselves. We formulate the blur identification problem as a constrained maximum likelihood problem. The constraints directly incorporate a priori 

Least squares restoration of multichannel images
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In this paper we consider the problem of multichannel restoration using both within-and between-channel deterministic information. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images

Restoration of color images by multichannel Kalman filtering
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A multichannel image is a set of image planes that exhibit between-plane correlations. Degradation of multichannel imagery involves both within-and between-channel blurs. Restoration of such images using existing independent-channel filters is not appropriateWe present a useful method for assessing the quality of a typewritten document image and automatically selecting an optimal restoration method based on that assessment. We use five quality measures that assess the severity of background speckle, touching characters

Blind iterative restoration of images with spatially-varying blur
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Removing non-uniform blur and noise from optical images is a very difficult problem to resolve. In this paper we describe a strategy that can be used for solving such problems. We describe how to restore images blurred by an unknown spatially-varying point spread

Digital restoration of indium-111 and iodine-123 SPECT images with optimized Metz filters
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MATERIALS AND METHODS Determination of Modulation Transfer Functions In digital image restoration , an estimate of the mod ulation transfer function (MTF) is used to characterize and partially correct for the blurring that occurs during acquisition. The MTFs

Diving into haze-lines: Color restoration of underwater images
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Underwater images suffer from color distortion and low contrast, because light is attenuated as it propagates through water. The attenuation varies with wavelength and depends both on the properties of the water body in which the image was taken and the 3D structure of theImage restoration using resolution expansion is important in many areas of image processing. This paper introduces a restoration method for low-resolution text images which produces expanded images with improved definition. This technique creates a strongly ABSTRACT A problem of restoration of images blurred by space-invariant point-spread functions (SIPSF) is considered. The SIPSF operator is factorized as a sum of two matrices. The first term is a polynomial of a noncirculant operator P and the second term is a Hankel

Filtration and restoration of satellite images using doubly stochastic random fields
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The paper is devoted to filtering algorithms of satellite images . Inadvisability of applying the simplest mathematical models of random fields with non-uniform filtering material is shown. We consider the comparative analysis of effectiveness of the filtering and calculate the gain Methods for image restoration which respect edges and other important features are of fundamental importance in digital image processing. In this paper, we present a novel technique for the restoration of images containing rotated (linearly transformed) rectangular

Restoration of Landsat-7 images
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The image restoration problem attempts to recover images that have been degraded by the limited resolution of the sensor as well as by the presence of noise. The resolution of images obtained by the satellite sensors is degraded by sources such as: optical diffraction, detector

An algorithm for blind restoration of blurred and noisy images
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This paper presents a technique for deblurring noisy images . It includes two processing blocks, one for denoising and another for blind image restoration . The denoising step is based on the theories of singular value decomposition and compression-based filtering. The

Maximum-A-Posteriori Restoration of Images -An Application of the Viterbi Algorithm to Two-Dimensional Filtering
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In many restoration problems, the a-priori knowledge of a finite number of pixel amplitudes of the original image is available (eg blurred blackand-white images ). It is shown how to incorporate this information into optimal image reconstruction. The degradation of a discreteIn this article, a new method for segmentation and restoration of images on two-dimensional surfaces is given. Active contour models for image segmentation are extended to images on surfaces. The evolving curves on the surfaces are mathematically described using a

Application of optical flow techniques in the restoration of non-uniformly warped images
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When viewing a scene through a turbulent atmosphere, received images will be non- uniformly distorted. A major component of this distortion is a random x and y shift at each point in the received image. A motion blurred but geometrically accurate prototype is

Multichannel blind restoration of images with space-variant degradations
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In this thesis, we cover the related problems of image restoration and depth map estimation from two or more space-variantly blurred images of the same scene in situations, where the extent of blur depends on the distance of scene from camera. This includes out- of -focus blur

Restoration of images corrupted by impulse noise using blind inpainting and l0 norm
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This article studies the problem of image restoration of observed images corrupted by impulse noise and other types of noise (eg zero-mean Gaussian white noise). Since the pixels damaged by impulse noise contain no information about the true image, these

Restoration of randomly blurred images via the maximum a posteriori criterion
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The maximum a posteriori estimation (MAP) technique is applied to the problem of restoring images distorted by noisy point spread functions and additive noise. The resulting MAP estimator is nonlinear and is obtained by numerically maximizing a conditional probability

EFDM: Restoration of single-sided low-quality document images
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This paper addresses the problem of restoration and enhancement of very old single-sided document images . At first step, a degradation model is developed for the generation of synthesized degraded document images in both double-sided and single-sided formats It is well known that the theoretical intensity at a point (x, y) from an astronomical image is given 1 ̃ Z (x, y)= S (x-x, y-y) h (x, y) dxdywhere S (,) represents the true underlying intensity and h (,) is the point spread function (psf)-However, when we consider discrete

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