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Intermediate level processing for a computer vision systemTing, David M. T. January 1979 (has links)
No description available.
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Digital Image Processing Using NTEC FacilitiesRoesch, James F. 09 1900 (has links) (PDF)
University of Central Florida College of Engineering Thesis / Digital image enhancement refers to the improvement of a given image for human interpretation. Digital image processing facilities are those in which hardware and software computing elements are combined in such a way as to enable the processing of digital images. This report describes the use of the Naval Training Equipment Center (NTEC) Computer Systems Laboratory computing facilities to enhance digital images. Described are two major hardware systems, the IKONAS RDS-3000 raster display graphics system and the VAX-11/780, and the digital image processing program (DIMPRP) written by the author. Digital image enhancement theory and practice are addressed through a discussion of the DIMPRP software. Finally, enhancements to the NTEC digital image processing facility such as improvements in hardware reliability, documentation, and increased speed of program esecution are discussed. / M.S.; / Engineering; / Engineering; / 78 p. / vii, 78 leaves, bound : ill. ; 28 cm.
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Recognition of occluded objects: a dominant point approach阮邦志, Yuen, Pong-chi. January 1993 (has links)
published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
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Restoration of quadratically distorted imagesKwon, Tae-hwan 24 July 1990 (has links)
The problem of the restoration of quadratically
distorted images is considered in this investigation, based
upon the fact that images formed by partially coherent
illuminations are related quadratically to the amplitude of
the object. Two of the most important problems in image
restoration are: 1) determining the degradation
characteristics of the degraded image and 2) developing
restoration algorithms. Among the two classes of inverse
problems, one for system identification and the second for
image restoration, only the means to solve the latter are
presented in this study.
Since the present problem is represented by the second-order
term of a Volterra series expansion, multidimensional
Volterra filter theory is presented with emphasis on the
properties of two-dimensional quadratic filter.
The mathematics of inverse problems is presented for
the purpose of image restoration, and the novel algorithms
which are simple and easy to implement and robust to the
ill-conditioned system in comparison to the existing
algorithms are proposed. Since quadratically distorted
imaging systems preclude a closed-form solution, approximate
solutions are obtained through application of the proposed
iterative and noniterative schemes. Images restored
approximately by the proposed algorithms can be improved
substantially by the use of a Newton-Raphson iteration
scheme.
Two typical regularization methods are presented and
the truncated singular-value decomposition method is applied
for the noisy image restoration. Regularized iterative
restoration schemes for the noisy image restoration are also
considered. Simulation examples for different issues are
presented. / Graduation date: 1991
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Compression and View Interpolation for Multiview ImageryRichter, Stefan January 2011 (has links)
No description available.
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Optimal control approach to image registrationSalako, Stephen Taiwo. January 2009 (has links)
Thesis (Ph.D.)--University of Texas at Arlington, 2009.
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Efficient Way of Reading Rotary Dial Utility Meter Using Image ProcessingSouare, Moussa January 2009 (has links)
Thesis(M.S.)--Case Western Reserve University, 2009 / Title from PDF (viewed on 2010-01-28) Department of Electrical Engineering and Computer Science -- Electrical Engineering Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center
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Regridding in nonrigid image registrationLin, Ting-hung. January 2008 (has links)
Thesis (Ph.D.) -- University of Texas at Arlington, 2008.
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Visual enhancement using multiple cues /Chen, Jia. January 2009 (has links)
Includes bibliographical references (p. 81-90).
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Image deblurring /Yuan, Lu. January 2009 (has links)
Includes bibliographical references (p. 129-140).
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