image registration is enabling in integrating complementary and heterogeneous information from multiple images, and is particularly important for high-quality healthcare. To improve registration efficiency and accurac...
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image registration is enabling in integrating complementary and heterogeneous information from multiple images, and is particularly important for high-quality healthcare. To improve registration efficiency and accuracy, in this paper, a two-resolution-scale registration approach is proposed. Firstly, to speed up calculation, the images will be decomposed into multi-scale and multi-band representation by steerable pyramid that outweighs wavelets by providing invariance for both translation and rotation. Then, to avoid transformation error accumulation and magnification during the parameter transmission in the traditional multi-scale registration, the registration will be performed only in the lowest-resolution scale and the highest-resolution scale. In the former scale, the global rotation and scaling parameters will be calculated rapidly and accurately, which then will be directly used to initialize optimization in the latter scale, where, the translation differences will be corrected. The experiments on medical images demonstrate that the proposed registration is of good performance.
This paper discusses the capabilities of the fractional differential approach for the detection of textural features in two-dimensional digital images and the involved Lateral Inhibition Principle, and fractional diff...
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This paper discusses the capabilities of the fractional differential approach for the detection of textural features in two-dimensional digital images and the involved Lateral Inhibition Principle, and fractional differential masks and algorithms of digital image. Firstly, the kinetic physical meaning of fractional differential and the relationship between fractional calculus and classical time-frequency analysis and the separability of two-dimensional fractional calculus on certain conditions are deduced. Secondly, the difference between two Gaussians receptive fields for fractional differential of digital image involved signalprocessing and biologic vision nerve model is discussed. An analysis of its Mach band is also included. Thirdly, the implements and parameters of eight n x n fractional differential masks, which are mutual central symmetric, on negative x-coordinate, positive x-coordinate, negative y-coordinate, positive y-coordinate, left lower diagonal, left upper diagonal, right lower diagonal, right upper diagonal respectively are discussed. Lastly, the numerical implementation algorithms of fractional differential mask for digital image are discussed. Numerical experiments show that the textural details enhance capabilities of fractional differential-based texture operator and are better than that of integral differential based one for rich-grained digital images.
作者：
Omid ShakerniaYi MaT. John KooShankar SastryDept. of Electrical Engineering & Computer Science
University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995
he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California
Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati
In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-mot...
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In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.
We discuss the imaging properties of Controlled-Drift Detectors at high photon occupancy that is when the analog waveform at the anode to be readout contains several pulses that may even be partially overlapping. This...
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We discuss the imaging properties of Controlled-Drift Detectors at high photon occupancy that is when the analog waveform at the anode to be readout contains several pulses that may even be partially overlapping. This condition is encountered when the detector is operated in integrate-readout mode at high count rates like in synchrotron experiments. The imaging information, i.e. the incident photon distribution along the column, is still preserved in the waveform and it can be reconstructed by means of a suitable multiple-pulse signalprocessing. We evaluated multiple-pulse processing based on the weighted least square algorithm in the most relevant operating conditions to assess the achievable resolution of pulse amplitude and position. This analysis allows definition of achievable performances and limitations of Controlled Drift Detectors in high-rate single-photon spectroscopic imaging of x-rays.
The fundamental assumption that is made while space-time adaptive processing (STAP) technique is considered is that the signal to be processed takes on the form of a sequence of coherent pulses. Frequency modulated co...
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The fundamental assumption that is made while space-time adaptive processing (STAP) technique is considered is that the signal to be processed takes on the form of a sequence of coherent pulses. Frequency modulated continuous wave (FMCW) systems are in widespread use because of their numerous advantages due among others to its non pulse character. It seems extremely important to look for a possibility of using STAP procedures in FMCW systems to make them even more attractive. The paper presents a simple analysis of a proposed approach to achieve this goal. A structure of the signal processor is presented and assumptions necessary to be fulfilled are defined. Effects of the proposed approach implementation in HF, I, and x bands are evaluated on the basis of selected parameters of the appropriate FMCW-STAP systems.
The development of effective control architectures for Intervention AUVs (I-AUV) is a very challenging task due to the inherent complexities of the environment and the necessity of the vehicle to come into contact wit...
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ISBN:
(纸本)9781424406340;142440634X
The development of effective control architectures for Intervention AUVs (I-AUV) is a very challenging task due to the inherent complexities of the environment and the necessity of the vehicle to come into contact with underwater structures without closed-loop supervision. Despite this, both the scientific and industrial communities are keen supporters of the development of I-AUV technology owing to the relevant cost saying opportunities they are potentially able to offer in a number of applications. In this article we describe a comprehensive control architecture designed to dock an I-AUV on a receiving structure, using sonar and video imageprocessing alongside navigation data from conventional sensors. The approach is based on custom developed sonar and video processing algorithms and the results are validated in real-time conditions by means of Ifremer's experimental underwater vehicle VORTEx.
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