Earth Observation using Satellite imagery is a challenging tool for analysis but is proved an effective tool in offering a wide coverage. Satellite hnagery is an important economical tool in accessing mineral explorat...
详细信息
ISBN:
(纸本)9781479936717
Earth Observation using Satellite imagery is a challenging tool for analysis but is proved an effective tool in offering a wide coverage. Satellite hnagery is an important economical tool in accessing mineral exploration. Mineral mapping using satellite imageprocessing is a large scale approach to exploit available minerals in the earth's crust. There are various satellite sensors to imply the presence of minerals. Each sensor has its own characteristics. Data fusion is the method of collecting and combining data from multiple sensors. In Geographic information systems, various data are used for spatial decision making. The relation between different set of data can be denoted in matrix format and its properties are used by analysing various algorithms. image fusion is used for combining the significant features which are captured by various image sensors. image sharpening, feature enhancement and image classification can be established using image Fusion algorithms. image fusion can be applied at various levels like decision, feature, and pixel level. Mineral exploration is done on the decision and feature level in GIS. In this paper, Principal component analysis method (PCA) was used for combining multi-source and multi-scale geo-information at pixel level for Hyperion and ALI data. Hybrid image is obtained by combining the values of pixels which is spatially based for different set of images and thus generated image is used for extracting the information or classification. Results obtained in this paper give the distribution which is of spatially based for mineral deposits in the study region with the help of AO-1 Hyperion and ALI data.
image diagnostics are becoming standard ones in nuclear fusion. At present, images are typically analyzed off-line. However, real-time processing is occasionally required (for instance, hot-spot detection or pattern r...
详细信息
image diagnostics are becoming standard ones in nuclear fusion. At present, images are typically analyzed off-line. However, real-time processing is occasionally required (for instance, hot-spot detection or pattern recognition tasks), which will be the objective for the next generation of fusion devices. In this paper, a test bed for image generation, acquisition, and real-time processing is presented. The proposed solution is built using a Camera Link simulator, a Camera Link frame-grabber, a PXIe chassis, and offers software interface with EPICS. The Camera Link simulator (PCIe card PCIe8 Dva C-Link from Engineering Design Team) generates simulated image data (for example, from video-movies stored in fusion databases) using a Camera Link interface to mimic the frame sequences produced with diagnostic cameras. The Camera Link frame-grabber (FlexRIO Solution from National Instruments) includes a field programmable gate array (FPGA) for image acquisition using a Camera Link interface;the FPGA allows for the codification of ad-hoc imageprocessingalgorithms using LabvIEW/FPGA software. The frame grabber is integrated in a PXIe chassis with system architecture similar to that of the ITER Fast Controllers, and the frame grabber provides a software interface with EPICS to program all of its functionalities, capture the images, and perform the required imageprocessing. The use of these four elements allows for the implementation of a test bed system that permits the development and validation of real-time imageprocessing techniques in an architecture that is fully compatible with that of the ITER Fast Controllers. This paper provides a specific example of a pattern search in a movie, its real-time implementation, and a performance analysis of the entire platform. (C) 2014 Elsevier B.v. All rights reserved.
We have analyzed the diffraction of a plane wave and a vortex beam on a circular micro-aperture in the near field (a few wavelengths away from the source) using different models and computation algorithms: the Reyleig...
详细信息
It is widely known that the wavelet coefficients of natural scenes possess certain statistical regularities which can be affected by the presence of distortions. The DIIvINE (Distortion Identification-based imageveri...
详细信息
It is widely known that the wavelet coefficients of natural scenes possess certain statistical regularities which can be affected by the presence of distortions. The DIIvINE (Distortion Identification-based imageverity and Integrity Evaluation) algorithm is a successful no-reference image quality assessment (NR IQA) algorithm, which estimates quality based on changes in these regularities. However, DIIvINE operates based on real-valued wavelet coefficients, whereas the visual appearance of an image can be strongly determined by both the magnitude and phase information. In this paper, we present a complex extension of the DIIvINE algorithm (called C-DIIvINE), which blindly assesses image quality based on the complex Gaussian scale mixture model corresponding to the complex version of the steerable pyramid wavelet transform. Specifically, we applied three commonly used distribution models to fit the statistics of the wavelet coefficients: (1) the complex generalized Gaussian distribution is used to model the wavelet coefficient magnitudes, (2) the generalized Gaussian distribution is used to model the coefficients' relative magnitudes, and (3) the wrapped Cauchy distribution is used to model the coefficients' relative phases. All these distributions have characteristic shapes that are consistent across different natural images but change significantly in the presence of distortions. We also employ the complex wavelet structural similarity index to measure degradation of the correlations across image scales, which serves as an important indicator of the subbands' energy distribution and the loss of alignment of local spectral components contributing to image structure. Experimental results show that these complex extensions allow C-DIIvINE to yield a substantial improvement in predictive performance as compared to its predecessor, and highly competitive performance relative to other recent no-reference algorithms. (C) 2014 Elsevier B.v. All rights reserved.
Compressive spectral imaging captures the spatial and spectral information of a scene using a set of two-dimensional random projections. Compressed sensing reconstruction algorithms are then used to recover the underl...
详细信息
ISBN:
(纸本)9781479928934
Compressive spectral imaging captures the spatial and spectral information of a scene using a set of two-dimensional random projections. Compressed sensing reconstruction algorithms are then used to recover the underlying threedimensional source. This work presents a new generation of devices that attain compressive spectral image measurements by means of a colored-patterned detector and a dispersive element. Simulations show that these new generation devices can recover spectral scenes with up to 5 dB gain in PSNR with respect to traditional Coded Aperture Snapshot Spectral Imaging (CASSI) systems.
This book contains the proceedings of the 4th International Conference on Data Analysis and processing held in Cefalu' (Palermo, ITALY) on September 23-25 1987. The aim of this Conference, now at its fourth editio...
ISBN:
(纸本)9781461310082
This book contains the proceedings of the 4th International Conference on Data Analysis and processing held in Cefalu' (Palermo, ITALY) on September 23-25 1987. The aim of this Conference, now at its fourth edition, was to give a general view of the actual research in the area of methods and systems for achieving artificial vision as well as to have an up-dated information of the current activity in Europe. A number of invited speakers presented overviews of statistical classification problems and methods, non conventional archi tectures, mathematical morphology, robotic vision, analysis of range images in vision systems, pattern matching algorithms and astronomical data processing. Finally a survey of the discussion on the contribution of AI to image Analysis is given. The papers presented at the Conference have been subdivided in four sections: knowledge based approaches, basic pattern recognition tools, multi features system based solutions, image analysis-applications. We must thank the IBM-Italia and the Digital Equipment Corpo ration for sponsoring this Conference. We feel that the days spent at Cefalu' were an important step toward the mutual exchange of scientific information within the imageprocessing community. v. Cantoni Pavia University v. Di Gesu' Palermo University S. Levialdi Rome University v CONTENTS INvITED LECTURES . . 3 Morphological Optics.
Unsupervised data clustering can be addressed by the estimation of mixture models, where the mixture components are associated to clusters in data space. In this paper we present a novel, unsupervised classification a...
详细信息
Unsupervised data clustering can be addressed by the estimation of mixture models, where the mixture components are associated to clusters in data space. In this paper we present a novel, unsupervised classification algorithm based on the simultaneous estimation of the mixture's parameters and the number of components (complexity). Its distinguishing aspect is the way the data space is searched. Our algorithm starts from a single component covering all the input space and iteratively splits components according to breadth first search on a binary tree structure that provides an efficient exploration of the possible solutions. The proposed scheme demonstrates important computational savings with respect to other state-of-the-art algorithms, making it particularly suited to scenarios where the performance time is an issue, such as in computer and robot vision applications. The initialization procedure is unique, allowing a deterministic evolution of the algorithm, while the parameter estimation is performed with a modification of the Expectation Maximization algorithm. To compare models with different complexity we use the Minimum Message Length information criteria that implement the trade-off between the number of components and data fit log-likelihood. We validate our new approach with experiments on synthetic data, and we test and compare to related approaches its computational efficiency in data-intensive image segmentation applications. (C) 2014 Elsevier B.v. All rights reserved.
This paper deals with multipath channel estimation for Orthogonal Frequency-Division Multiplexing systems under slow to moderate fading conditions. Most of the conventional methods exploit only the frequency-domain co...
详细信息
This paper deals with multipath channel estimation for Orthogonal Frequency-Division Multiplexing systems under slow to moderate fading conditions. Most of the conventional methods exploit only the frequency-domain correlation by estimating the channel at pilot frequencies, and then interpolating the channel frequency response. More advanced algorithms exploit in addition the time-domain correlation, by employing Kalman filters based on the approximation of the time-varying channel. Adopting a parametric approach and assuming a primary acquisition of the path delays, channel estimators have to track the complex amplitudes of the paths. In this perspective, we propose a less complex algorithm than the Kalman methods, inspired by second-order Phase-Locked Loops. An error signal is created from the pilot-aided Least-Squares estimates of the complex amplitudes, and is integrated by the loop to carry out the final estimates. We derive closed-form expressions of the mean squared error of the algorithm and of the optimal loop coefficients versus the channel state, assuming a Rayleigh channel with lakes' Doppler spectrum. The efficiency of our reduced complexity algorithm is demonstrated, with an asymptotic mean squared error lower than the first-order auto-regressive Kalman filters reported in the literature, and almost the same as a second-order Kalman-based algorithm. (C) 2013 Elsevier B.v. All rights reserved.
In this paper, hardware optimization of the preprocessing and software implementation of the processing blocks of a computer-aided semen analysis (CASA) system are proposed, which is also implemented on an FPGA and AR...
详细信息
暂无评论