The integration of multi-source ancillary data is one of the most promising techniques for improved classification of remotesensingimages. In this research a classification strategy based on possibility theory and f...
详细信息
The integration of multi-source ancillary data is one of the most promising techniques for improved classification of remotesensingimages. In this research a classification strategy based on possibility theory and fuzzy subsets was applied in order to combine spectral and ancillary information. The ancillary information was used to define expert rules on the geographic context of the different land use classes. The method was tested on a complex, rugged area in Central Switzerland. Special emphasis was laid on the pre-processing of the Landsat TM image. A new physical based radiometric correction was applied to the imagery in order to eliminate the impact of atmosphere and slope-aspect effects. Due to the integration of ancillary information by possibility theory a notable accuracy improvement was achieved in comparison to a Maximum-Likelihood classifier with nonparametric priors.
In areas as diverse as earth remotesensing, astronomy, and medical imaging, image acquisition technology has undergone tremendous improvements in recent years. The vast amounts of scientific data are potential treasu...
详细信息
In areas as diverse as earth remotesensing, astronomy, and medical imaging, image acquisition technology has undergone tremendous improvements in recent years. The vast amounts of scientific data are potential treasure-troves for scientific investigation and analysis. Unfortunately, advances in our ability to deal with this volume of data in an effective manner have not paralleled the hardware gains. While special-purpose tools for particular applications exist, there is a dearth of useful general-purpose software tools and algorithms which can assist a scientist in exploring large scientific image databases. This paper presents our recent progress in developing interactive semi-automated image database exploration tools based on patternrecognition and machine learning technology. We first present a completed and successful application that illustrates the basic approach: the SKICAT system used for the reduction and analysis of a 3 terabyte astronomical data set. SKICAT integrates techniques from imageprocessing, data classification, and database management. It represents a system in which machine learning played a powerful and enabling role, and solved a difficult, scientifically significant problem. We then proceed to discuss the general problem of automated image database exploration, the particular aspects of image databases which distinguish them from other databases, and how this impacts the application of off-the-shelf learning algorithms to problems of this nature. A second large image database is used to ground this discussion: Magellan's images of the surface of the planet Venus. The paper concludes with a discussion of current and future challenges.
A prototype binary edge-extracting ('smart') custom image sensor array, 'Edge 1', was developed previously at the University of Brighton, Awcock. It was implemented in a 2 micron ES2 CMOS process and f...
详细信息
A prototype binary edge-extracting ('smart') custom image sensor array, 'Edge 1', was developed previously at the University of Brighton, Awcock. It was implemented in a 2 micron ES2 CMOS process and featured 72 I/O pins because of its total lack of on-chip support circuitry. Several detail changes were suggested by testing this prototype and many of these have been recently tested in a 1.5 micron ES2 CMOS re-implementation of this design, 'Edge 2'. The successful operation of the Edge 1 prototype has shown that general-purpose CMOS manufacturing processes such as that offered by ES2 are indeed a practical proposition for the integration of imagesensing and processing functions. The uniformity of the photo-sites produced has been very encouraging.
This article deals with the processing of already classified satellite images according to land use in order to remove ambiguities, i.e. mistakes in labels. Those images have already been classified with the maximum l...
详细信息
This article deals with the processing of already classified satellite images according to land use in order to remove ambiguities, i.e. mistakes in labels. Those images have already been classified with the maximum likehood method but some classes are not correctly determined. For the elimination of ambiguities in this kind of class, we applied our method of determination of land use mixture in pixels. We first briefly review our method of determination of land use mixture. Then we explain how we deal with ambiguities in labels of the maximum likehood classification. We finish with three examples of satellite images that have not correctly been classified. The first one is the vineyard case. Another example for naked soil and urban zone. The last one is a forestry survey application, the determination of the planted pines density.
Fingerprint verification systems are expensive and complex, requiring sensing facilities, pre-processing algorithms for image quality enhancement and procedures for ridge and minutiae detection which can be used for c...
详细信息
ISBN:
(纸本)0780326288
Fingerprint verification systems are expensive and complex, requiring sensing facilities, pre-processing algorithms for image quality enhancement and procedures for ridge and minutiae detection which can be used for classification, verification and recognition. To-date, the main published approaches to fingerprint recognition break down the process of ridge detection into smoothing or early pre-processing, edge detection, thresholding, binarization and subsequently thinning. This whole procedure can be very computationally expensive and hence require more expensive hardware to meet the response-time requirements. The approach presented in this paper is based on fuzzy logic techniques. This has the advantage of being simple and less expensive.
We have developed a device called Active Eye sensing System which is consisted of stereo camera. Each camera has 2 DOF that gives a wide view of 3D space. Using AESS, we extract a moving object from the scene, keep tr...
详细信息
ISBN:
(纸本)0780330269
We have developed a device called Active Eye sensing System which is consisted of stereo camera. Each camera has 2 DOF that gives a wide view of 3D space. Using AESS, we extract a moving object from the scene, keep tracking, and give its position and velocity. High speed correlation Method is used to achieve realtime imageprocessing. As one of applications, we have exhibited NetWork Neuro Baby in SIGGRAPH'95 held in Los Angeles.
Groundwater management nowadays is mainly governed by hydrogeological aspects of groundwater occurrences. However, focussing on groundwater as a natural resource of the landscape, there is a deficit in spatial informa...
详细信息
ISBN:
(纸本)0819416444
Groundwater management nowadays is mainly governed by hydrogeological aspects of groundwater occurrences. However, focussing on groundwater as a natural resource of the landscape, there is a deficit in spatial information about the ecological factors influencing the water balance. It becomes more important to assess the ecological role of groundwater in accordance to its quality and quantity as well as to predict risks by changes in the landscape such as lowering groundwater level and nitrate leaching. Due to high spatial diversity in the pattern of land use, relief attributes and soil properties, ecological data have to distinguish different homogeneous site units. remotesensing data with high resoluted geometry would have the potential to improve the spatial information about landscape and its water balance. In many regions an aggravating deficit between the groundwater consumption and the recharge of groundwater can be observed. This situation is characterized by two effects: (1) Increasing groundwater consumption. (2) Decreasing recharge of groundwater. A higher level of surface sealing can be found in agriculture as well as in urban areas. Evapotranspiration in plant production has increased. By intensification in agriculture plant production has generated more biomass and crop yield. But for every unit of yield and biomass, the plant has to transpirate additional soil water. Therefore, higher intensity in farming is related to higher water consumption by the process of evapotranspiration.
The proceeding contains 226 papers. Topics discussed include underwater and acoustic applications in signal processing, environmental sensing, design and implementation of signal processing systems, signal processing ...
详细信息
The proceeding contains 226 papers. Topics discussed include underwater and acoustic applications in signal processing, environmental sensing, design and implementation of signal processing systems, signal processing in astronomy and space physics, biomedical imaging, neurological signal processing, automotive signal processing, echo cancellation, audio and electroacoustics, wideband coding, time delay estimation and equalization, hardware for image and video coding, neural network application to speech processing, patternrecognition, language identification, arrays and underwater acoustics, system identification and classification, sonar beamforming, and radars.
This paper deals with the problem of unsupervised classification of images modeled by Markov Random Fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (simul...
详细信息
ISBN:
(纸本)0818670428
This paper deals with the problem of unsupervised classification of images modeled by Markov Random Fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (simulated annealing, ICM, etc...). However, when they are not known, the problem becomes more difficult. One has to estimate the hidden label field parameters from the only observable image. Our approach consists of extending a recent iterative method of estimation, called Iterative Conditional Estimation (ICE) to a hierarchical markovian model. The idea resembles the Estimation-Maximization (EM) algorithm as we recursively look at the Maximum a Posteriori (MAP) estimate of the label field given the estimated parameters then we look at the Maximum Likelihood (ML) estimate of the parameters given a tentative labeling obtained at the previous step. We propose unsupervised image classification algorithms using a hierarchical model. The only parameter supposed to be known is the number of regions, all the other parameters are estimated. The presented algorithms have been implemented on a Connection Machine CM200. Comparative tests have been done on noisy synthetic and real images (remotesensing).
Nonlinear modeling and solution techniques of array algebra are applied to the problem of simultaneous graph matching and photogrammetric bundle adjustment. Graph matching provides automatically the image coordinates ...
详细信息
ISBN:
(纸本)0819418390
Nonlinear modeling and solution techniques of array algebra are applied to the problem of simultaneous graph matching and photogrammetric bundle adjustment. Graph matching provides automatically the image coordinates and 2 × 2 weight matrices of `control entities', points and vertices of known relative geometrical shape which replace the control points used in traditional bundle adjustment. Inclusion of multiple control entities to cover the entire image area of interest allows the use of a fast new array algebra formation of real-time bundle adjustment to act as the pull-in mechanism for the global graph matching process. The resulting integrated solution of Feature Entity Least Squares Matching (FELSM) is very fast and produces high quality results. FELSM has demonstrated solutions to several problems of ongoing research interest in photogrammetry and the related fields of image understanding, patternrecognition and computer vision. These results open the way for further integration of the various fields.
暂无评论