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Boaz Cohen, Ben-Gurion University of the Negev (Israel)
Its'hak Dinstein, Ben-Gurion University of the Negev (Israel)
The method for reconstruction and restoration of super resolution images from low resolution sequences presented here is an extension of Irani and Peleg's algorithm (""Improving Resolution by Image Registration'', CVGIP: Graphical Models and Image Processing, Vol. 53, No. 3, pp. 231-239, 1991). The input is a set of low resolution images that have been registered to a pixel translation accuracy. A high resolution image is initialized and iteratively improved by back-projecting the errors between the low resolution images and the respective images obtained by simulating the imaging system. The sub-pixel translations between the low resolution images are quantized. The imaging system's PSF and back projection function are estimated with a resolution higher than that of the super resolution image and decimated so that two banks of polyphase filters are obtained. The use of the polyphase filters allows exploitation of all the input images without any smoothing or interpolation operations.
ic981156.pdf (From Postscript)
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Samuel Foucher, Universite de Sherbrooke (Canada)
Goze B Bénié, Universite de Sherbrooke (Canada)
Jean-Marc Boucher, ENSTB (France)
Radar images are affected by a multiplicative noise depending on the underlying signal (the ground reflectivity) due to the coherence of the radar wavelength. Images present a strong pixel to pixel variability considerably reducing the efficiency of target detection and classification algorithms. We propose in this study filtering this noise using image multiresolution analysis. The value of the wavelet coefficients of the radar reflectance is estimated by a Bayesian model by maximizing the a posteriori density and by modeling the different densities using the Pearson distributions system. The resulting filter combines a classical adaptive approach and wavelet decompostion using the local variance of the wavelet coefficients for segmenting and weighting the latter taking into account the multiplicative nature of the noise.
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Kaaren L May, Imperial College (U.K.)
Tania Stathaki, Imperial College (U.K.)
Aggelos K Katsaggelos, Northwestern University (U.S.A.)
A new method of incorporating local image characteristics into blind image restoration is proposed. The local variance of the degraded image is used as a measure of spatial activity, from which individual pixel bounds are determined. A parameter defined by the user controls the degree of smoothing. The local bounds define the solution more precisely than smoothness constraints on the image (including those that are spatially-adaptive), reducing the number of possible solutions and leading to a faster rate of convergence. Experimental results demonstrate the potential of this method as an alternative/supplement to smoothing constraints in blind image restoration.
ic981493.pdf (From Postscript) TOP
Yibin Zheng, GE Corporate R&D (U.S.A.)
Peter C Doerschuk, Purdue University (U.S.A.)
John E Johnson, The Scripps Research Institute (U.S.A.)
An interpolation problem that is important in viral x-ray crystallography is considered. The problem requires new methods because (1) the function is known to have icosahedral symmetry, (2) the data is corrupted by experimental errors and therefore lacks the symmetry, (3) the problem is 3D, (4) the measurements are irregularly spaced, and (5) the number of measurements is large (10**4). A least-squares approach is taken using two sets of basis functions: the functions implied by a minimum-energy band-limited exact interpolation problem and a complete orthonormal set of band-limited functions. A numerical example on Cowpea Mosaic Virus is described.
ic981494.pdf (From Postscript) TOP
Farzam Farbiz, Amirkabir University of Technology (Iran)
Seyed Ahmad Motamedi, Amirkabir University of Technology (Iran)
Mohammad Bagher Menhaj, Amirkabir University of Technology (Iran)
This paper presents a new filtering approach based on fuzzy-logic which has high performance in mixednoise environments. This filter is mainly based on the idea that each pixel is not allowed to be uniformly fired by each of the fuzzy rules. We perform several test experiments in order to highlight the merit of the proposed method. The results are very promising and indicating the high performance of the proposed filter in image restoration in compared with the filters which have been recently cited in image processing literature.
ic982259.pdf (Scanned) TOP
Carlotta Domeniconi, University of California, Riverside (U.S.A.)
Sibel Tari, University of California, Riverside (U.S.A.)
Ping Liang, University of California, Riverside (U.S.A.)
An original technique, based on ridge point detection directly from gray scale fingerprint images, is proposed. Our method avoids serious problems that algorithms which perform binarization of fingerprint images have. Each step can be easily hardware implemented, allowing a relevant speed up of the whole process.
ic982346.pdf (From Postscript) TOP
Nikki M Bruner, Oklahoma State University (U.S.A.)
Rao Yarlagadda, Oklahoma State University (U.S.A.)
Diffusion of the attractor or reconstructed image of the fractal code provides us a technique to restore edge information. Because of coding error associated with the fractal mappings, edges are degraded at high compression rations. Partitioning compensates for the degradation, but lowers the compression ratios significantly and does not insure the retention of significant edges. The diffusion technique uses the image gradient to control the rate and direction of diffusion. This allows for smoothing in flat (low intensity transitions) regions and sharpening in edge (high intensity transitions) regions. The usage of the image gradient in this method insures the retention of significant edges. The diffusion technique presented in this paper lessens the degree of degradation of edges from fractal coding at a lower bit rate cost than partitioning at small blocks sizes.
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Farhan A Baqai, Purdue University (U.S.A.)
Jan P Allebach, Purdue University (U.S.A.)
We incorporate a higher order measurement-based model for printer dot interactions within the iterative direct binary search (DBS) halftoning algorithm. We also present an efficient strategy for evaluating the change in computational cost as the search progresses. Experimental results are shown which demonstrate the efficacy of the approach.
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Valerie Chickanosky, University of Vermont (U.S.A.)
Gagan Mirchandani, University of Vermont (U.S.A.)
Wreath product group based spectral analysis has led to the development of the wreath product transform, a new multiresolution transform closely related to the wavelet transform. In this work, we derive the filter bank implementation of a simple wreath product transform and show that it is in fact, a multiresolution Roberts edge detector. We also derive the relationship between this transform and the two-dimensional Haar wavelet transform. We prove that using a nontraditional metric for measuring edge amplitude with the wreath product transform yields a rotation and translational invariant edge detector. We introduce a novel method for measuring the orientation of an edge and show that it is without error in the noise-free case. Wreath product edge detection performance is shown to be superior to many standard edge detectors.
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Jacky Chun Kit Yan, University of Toronto (Canada)
Patrizio Campisi, Universita degli Studi di Roma Tre (Italy)
Dimitrios Hatzinakos, University of Toronto (Canada)
In this paper, we propose a noise filtering scheme, which is based on a multichannel homomorphic transformation, for color photographic images corrupted by signal-dependent film grain noise. The proposed method performs the estimation of the noise parameter using the higher-order statistics (skewness or kurtosis) of the corrupted image and the filtered image statistics. This parameter estimation technique can be used to generate color film grain noise that has applications in motion picture productions. After a theoretical description of the method employed, experimental results are provided.
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