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Contrast enhancement technique based on local detection of edges
COMPUTERVISION, GRAPHICS,AND IMAGE PROCESSING45, 399-400 (1989)
Abstracts of Papers Accepted for Publication PAPERS Enhancement Technique Based on Local Detection of Edges. AEEDDINE BEGHDADI AND ALAIN EE NEGRATE. Groupe d’Analyse dImages Biomedicales, Universite Ret@ Descartes, 3, Bld Pasteur, 75015 Paris, France. Received January 21, 1988; accepted October 28, 1988.
Cotttravt
A digital processing technique is proposed in order to enhance image contrast without significant noise enhancement. The technique, derived from Gordon’s algorithm, accounts for visual perception criteria, namely for contour detection. The efficiency of our algorithm is compared to Gordon’s one and to the classical ones.
to Linear Two- View Moth Algorithms. XINHUA ZHUANG. Department of Computer Science and Bngineering, Zhejiang University, Hangxhou, People’s Republic of China. Received June 3, 1986; accepted October 28,1988.
A Simp&fication
This note provides a simplification to linear two-view motion algorithms by avoiding the second decomposition of motion parameter matrix E required by all existing linear algorithms.
Fmctal-Based Modeling.
Ana&&
and Inteqwhtion
of 3D Natural
Staface
Shqes
and Their
Application
to Terrain
NAOKAZU YOKOYA AND KAZIJHIKO YAMAMOTO. Electrotechnical Laboratory, Tsukuba Science City, Ibaraki 305, Japan. NOBORU FUNAKUBO. Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191, Japan. Received January 51988; revised November 4, 1988.
This paper describes the fractal-based analysis and interpolation of 3D natural surface shapes and their application to terrain modeling in a sensor simulation for an earth resource satellite. After introducing the fractional Brownian function as a mathematical model for describing natural fractals and discussing its properties, we present fractal-based techniques for analyzing and interpolating 3D surface shapes. These techniques are essentially based on the approximation of the surface by the fractional Brownian function. Finally, the application of these techniques to terrain modeling is described. The analysis-followed-by-interpolation method is successfully applied for generating the digital terrain map of high spatial resolution from the existing coarse terrain data.
Method fw Locating the Focus of Expansion. SHAHR~ARNEGAHDAIUPOUR. Department of Electrical Engineering, University of Hawaii at Manoa, Honolulu, Hawaii %822. BERTHOLD K. P. HORN. MIT Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139. Received December 10, 1986; revised October 18, 1988.
A Direct
We address the problem of recovering the motion of a monocular observer relative to a rigid scene. We do not make any assumptions about the shapes of the surfaces in the scene, nor do we use estimates of the optical flow or point correspondences. Instead, we exploit the spatial gradient and the time rate of change of brightness over the whole image and explicitly impose the constraint that the surface of an object in the scene must be in front of the camera for it to be imaged. 399 0734189X/89 $3.00 Copyright 0 1989 by Academic Press, Inc. AI1 rights of reproduction in any form reserved.
Abstracts of Papers Accepted for Publication PAPERS Enhancement Technique Based on Local Detection of Edges. AEEDDINE BEGHDADI AND ALAIN EE NEGRATE. Groupe d’Analyse dImages Biomedicales, Universite Ret@ Descartes, 3, Bld Pasteur, 75015 Paris, France. Received January 21, 1988; accepted October 28, 1988.
Cotttravt
A digital processing technique is proposed in order to enhance image contrast without significant noise enhancement. The technique, derived from Gordon’s algorithm, accounts for visual perception criteria, namely for contour detection. The efficiency of our algorithm is compared to Gordon’s one and to the classical ones.
to Linear Two- View Moth Algorithms. XINHUA ZHUANG. Department of Computer Science and Bngineering, Zhejiang University, Hangxhou, People’s Republic of China. Received June 3, 1986; accepted October 28,1988.
A Simp&fication
This note provides a simplification to linear two-view motion algorithms by avoiding the second decomposition of motion parameter matrix E required by all existing linear algorithms.
Fmctal-Based Modeling.
Ana&&
and Inteqwhtion
of 3D Natural
Staface
Shqes
and Their
Application
to Terrain
NAOKAZU YOKOYA AND KAZIJHIKO YAMAMOTO. Electrotechnical Laboratory, Tsukuba Science City, Ibaraki 305, Japan. NOBORU FUNAKUBO. Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191, Japan. Received January 51988; revised November 4, 1988.
This paper describes the fractal-based analysis and interpolation of 3D natural surface shapes and their application to terrain modeling in a sensor simulation for an earth resource satellite. After introducing the fractional Brownian function as a mathematical model for describing natural fractals and discussing its properties, we present fractal-based techniques for analyzing and interpolating 3D surface shapes. These techniques are essentially based on the approximation of the surface by the fractional Brownian function. Finally, the application of these techniques to terrain modeling is described. The analysis-followed-by-interpolation method is successfully applied for generating the digital terrain map of high spatial resolution from the existing coarse terrain data.
Method fw Locating the Focus of Expansion. SHAHR~ARNEGAHDAIUPOUR. Department of Electrical Engineering, University of Hawaii at Manoa, Honolulu, Hawaii %822. BERTHOLD K. P. HORN. MIT Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139. Received December 10, 1986; revised October 18, 1988.
A Direct
We address the problem of recovering the motion of a monocular observer relative to a rigid scene. We do not make any assumptions about the shapes of the surfaces in the scene, nor do we use estimates of the optical flow or point correspondences. Instead, we exploit the spatial gradient and the time rate of change of brightness over the whole image and explicitly impose the constraint that the surface of an object in the scene must be in front of the camera for it to be imaged. 399 0734189X/89 $3.00 Copyright 0 1989 by Academic Press, Inc. AI1 rights of reproduction in any form reserved.