ISSN:0899-9457    

DOI:10.1002/ima.1850060402

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractA new facet of image restoration research has begun to emerge in recent years: super‐resolution of images, which we define as the processing of an image so as to recover object information from beyond the spatial frequency bandwidth of the optical system that formed the image. Simple Fourier analysis would indicate that super‐resolution is not possible. Therefore, it is important to reconcile this simplistic view with the existing algorithms that have been demonstrated to achieve super‐resolution. In this article, we consider some of the algorithms that have demonstrated super‐resolution and discuss the common principles that they share which makes it possible for them to recover some of the lost bandwidth of the object. We also consider the question of super‐resolution performance, which is the measure of how much lost bandwidth can be recovered from a super‐resolution algorithm, and how the performance is related to the algorithm principles that allow super‐resolution to occur. We conclude with examples of sup

ISSN:0899-9457    

DOI:10.1002/ima.1850060403

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractThis article develops an iterative spatially adaptive regularized image restoration algorithm. The proposed algorithm is based on the minimization of a weighted smoothing functional. The weighting matrices are defined as functions of the partially restored image at each iteration step. As a result, no prior knowledge about the image and the noise is required, but the weighting matrices as well as the regularization parameter are updated based on the restored image at every step. Conditions for the convexity of the weighted smoothing functional and for the convergence of the iterative algorithm are established for a unique global solution which does not depend on initial conditions. Experimental results are shown with astronomical images which demonstrate the effectiveness of the proposed algorithm.

ISSN:0899-9457    

DOI:10.1002/ima.1850060404

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractThis article reviews pixon‐based image reconstruction, which in its current formulation uses a multiresolution language to quantify an image's algorithmic information content (AIC) using Bayesian techniques. Each pixon (or its generalization, theinformation) represents a fundamental quanta of an image's AIC, and an image's pixon basis represents the minimum degrees of freedom necessary to describe the image within the accuracy of the noise. We demonstrate with a number of examples that pixon‐based image reconstruction yields results consistently superior to popular competing methods, including maximum likelihood and maximum entropy methods. Typical improvements include higher spatial resolution, greater sensitivity to faint sources, and immunity to the production of spurious sources and signal correlated residuals. Finally, we show how the pixon provides a generalization of the Akaike information criterion, and how it relates to concepts of “coarse graining” and the role of the Heisenberg uncertainly principle in statistical mechanics, provides a mechanism for optimal data compression, and represents a more optimal basis for image compression or reconstruction than w

ISSN:0899-9457    

DOI:10.1002/ima.1850060405

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractMultiresolution transforms, including a wavelet transform, are applied simage visualization, image restoration, filtering and compression, × object detection. Variance stabilization is used, when appropriate, cater for common astronomical image noise models. We discuss idation of such methods in the case of astronomical image processing. A range of examples illustrate the effectiveness of this aproach in handling point source and extended astronomical objects

ISSN:0899-9457    

DOI:10.1002/ima.1850060406

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractWhen spherical aberration was found to be degrading the performance of the Hubble Space Telescope (HST), great interest in image restoration methods arose in the astronomical community. The Richardson‐Lucy (RL) method became the preferred tool for restoring such data which typically has Poisson noise characteristics and a low signal‐to‐noise ratio. Subsequently, corrective optics were inserted into the telescope which is now operating close to the original specifications. However, generalized RL methods and some new techniques based on projections onto convex sets have proved useful both for the present HST data, which are often insufficiently sampled, and also for many other classes of astronomical images. The ST‐ECF staff have worked extensively in this and related areas, and some of these developments and their application to real data are de

ISSN:0899-9457    

DOI:10.1002/ima.1850060407

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractA new type of robust numeric solution of one form of the Fredholm integral equations of the first king has been discovered. This discovery has its most immediate and important applications in the deconvolution or deblurring of data acquired using scientific instruments. A solution of this integral equation has very general applications. For example, investigator‐controlled mapping of the instrumental point‐spread function to a more useful form is made feasible. The solution of the linear systems imaging model integral equation results from operations performed on the instrumental kernel, response, or point‐spread function with the direct result being the production of a robust, effective inverse kernel. The effective inverse is robust even in the presence of noise. The generation of the inverse kernel in no way depends on the observational data. Therefore, the image enhancement produced by this method contrasts with other numeric schemes that operate only on the observed data. This is an important distinction. This technique, which uses simple numeric operations, offers the possibility of attaining real‐time data enhancements for observational instruments. The concept of taking control of the instrument kernel or point‐spread function forms the basis of the work presented. Investigations of the application of artificial neural networks to resolution enhancement of Hubble Space Telescope imagery have led to a novel extended instrument paradigm that permits reliable and robust resolution enhancement. In addition to resolution enhancement, the fruits of this investigation have provided a powerful data mapping tool that permits nontrivial, numeric apodization of observed data. The applications of the novel convolution connection paradigm neural network has a great potential for multidisciplinary applications such as resolution enhancement of image and spec

ISSN:0899-9457    

DOI:10.1002/ima.1850060408

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractA non‐Bayesian approach to inverse problems is discussed in terms of the image restoration problem. The approach is based on the extended notion of the feasible estimate and on the Occam's principle of choosing the simplest object, consistent with the data. The Occamian estimation is performed by transforming the inverse or maximum likelihood estimate to its principal components, which are induced by Fisher's information matri

ISSN:0899-9457    

DOI:10.1002/ima.1850060409

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractIn this work, we examine simple to complex methods proposed within the Bayesian paradigm to perform image restoration in astronomy. We start by describing the classical conditional and simultaneous autoregressions, then we move on to study how to incorporate smoothness constraints to the classical Richardson‐Lucy restoration method and also how to modify the image scale and define prior models on other scales than the linear one. Finally, we compare those models on images of Jupiter after the impacts of the fragments of the comet Shoemaker‐Levy 9 at two waveleng

ISSN:0899-9457    

DOI:10.1002/ima.1850060410

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY

摘要:

AbstractThe mathematic problem of restoring an image degraded by blurring and noise is ill‐posed, so that the solution is affected by numeric instability. As a consequence, the solution provided by the so‐called inverse filter is completely contaminated by noise and, in general, is deprived of any physical meaning. If one looks for approximate solutions, the ill‐posedness of the problem implies that the set of these solutions is too broad. For this reason, one must look for approximate solutions satisfying some kind ofa prioriconstraints, the so‐calleda prioriinformation. This fact explains the variety of methods, usually called regularization methods, which have been designed for solving this kind of problems. In this article we briefly review some of the most widely used methods, both deterministic and probabilistic, and show their effectiveness in the restoration of some HST

ISSN:0899-9457    

DOI:10.1002/ima.1850060411

出版商:John Wiley&Sons, Inc.    

年代:1995

数据来源: WILEY