Statistical Learning Theory-based Support Vector Machine (SVM), which is a supervised learning mechanism, can get good class rate in remotesensingimage classification. But manual obtaining of labeled training sample...
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In the edge detection of RS building image, the useful detail losing and the spurious edge often appear, To solve the problem. we used the dyadic wavelet to detect the edge of surface features by combining the edge de...
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ISBN:
(纸本)0780385543
In the edge detection of RS building image, the useful detail losing and the spurious edge often appear, To solve the problem. we used the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, we obtained the RS building image of a certain appropriate scale, and figured out the edge data of the plane and the upright directions respectively, then worked out the grads vector module of the surface features, at last by tracing them we got the edge data of the buildings therefore builded the RS image which obtained the checked edge. This method can depress the effect of noise and examine exactly the edge data of the building object by rule and line. With an experiment of RS building image, we certificated the feasibility of the application of dyadic wavelet in the RS building image edge detection.
For interferometric SAR processing (InSAR), the quality of the interferogram is affected by many factors such as Doppler Centroid difference, baseline, atmospheric effect., It can be measured by the estimation of the ...
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For interferometric SAR processing (InSAR), the quality of the interferogram is affected by many factors such as Doppler Centroid difference, baseline, atmospheric effect., It can be measured by the estimation of the coherence of the data. It has been shown that the coherence image can be used to do the classification in the area such as water, soil, plants, city or something else. But the coherence estimation is always biased somehow. To find an asymptotically unbiased coherence estimation method is therefore challenging and important for InSAR pcocessing. In this paper, several different coherence estimators are introduced. An accurate coherence computation method using an existing DEM is proposed and illustrated.
Eyetracking is one of the latest technologies that has shown potential in several areas including human-computer interaction for people with and without disabilities, and for noninvasive monitoring, detection, and eve...
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ISBN:
(纸本)0819453609
Eyetracking is one of the latest technologies that has shown potential in several areas including human-computer interaction for people with and without disabilities, and for noninvasive monitoring, detection, and even diagnosis of physiological and neurological problems in individuals. Current non-invasive eyetracking methods achieve a 30 Hz rate with possibly low accuracy in gaze estimation, that is insufficient for many applications. We propose a new non-invasive visual eyetracking system that is capable of operating at speeds as high as 6-12 KHz. A new CCD video camera and hardware architecture is used, and a novel fast imageprocessing algorithm leverages specific features of the input CCD camera to yield a real-time eyetracking system. A field programmable gate array (FPGA) is used to control the CCD camera and execute the imageprocessing operations. Initial results show the excellent performance of our system under severe head motion and low contrast conditions.
The purpose of the present work is the count and classification of the individuals in the wolf packs by processing its audio signals, supposing that we have recordings of sufficient temporary length, obtained with a s...
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The purpose of the present work is the count and classification of the individuals in the wolf packs by processing its audio signals, supposing that we have recordings of sufficient temporary length, obtained with a single microphone. We will set out an architecture that includes the treatment of the environmental background noise, the separation of signals and its classification.
Using video camera to manage the cars is gradually adopted in many kinds of applications, such as electric payment in the tollgate and car parking management. An automatic recognition model of automobile's license...
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ISBN:
(纸本)0780381939
Using video camera to manage the cars is gradually adopted in many kinds of applications, such as electric payment in the tollgate and car parking management. An automatic recognition model of automobile's license plate number is proposed in this paper. The designed system is expected to have high recognition accuracy and reliability such that the goal of automatic recognition can be achieved. We present a system to recognize the license number in the acquired image captured from a video camera. The recognition process of our system contains four major steps. First, the system tries to locate the probable position of the license plate within the acquired image by using gradient analysis and imageprocessing. Second, our model estimates the image parameters needed to normalize the license plate and uses the cross-correlation to detect the skew of the license plate and rectify the tilt. Third, we use a template technique to recognize the characters in the license plate. Finally, we use the information gained from the previous step to analyze the probable license numbers. We will illustrate the designing processes and give the experimental results from the proposed model. Based on the experimental results, the proposed system can effectively recognize the license number. The time needed to recognize a license plate takes only 1.5 second.
This paper introduces the use of aerial RGB digital photography to detect changes in soil structure at field level before vegetation appearance and in the early stages of crop development. Aerial digital photographs o...
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ISBN:
(纸本)0819451606
This paper introduces the use of aerial RGB digital photography to detect changes in soil structure at field level before vegetation appearance and in the early stages of crop development. Aerial digital photographs of a field trial were used as basis for soil structure mapping. images were acquired right after sowing the crop, and image-processing routines made it possible to detect and map changes in soil structure. The detected pattern could be recognized in the growth pattern of the canopy a month later. The field trial used in this work was subdivided into areas receiving different amounts of fertilizer, and the aerial digital photographs clearly showed the detected soil variations to overpower the influence of the differences in fertilization.
The Modulation Transfer Function (MTF) is a major parameter for high resolution optical remotesensing systems, indicating how spatial frequencies are transmitted and weakened by the imaging global chain. Assessing MT...
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ISBN:
(纸本)0819455172
The Modulation Transfer Function (MTF) is a major parameter for high resolution optical remotesensing systems, indicating how spatial frequencies are transmitted and weakened by the imaging global chain. Assessing MTF is thus a very important task during both the in-flight commissioning period and the routine monitoring phases. Classical in flight MTF measurement methods are based upon devoted well known patterns such as knife edge patterns. These techniques induce heavy constraints upon satellite payload programming taking into account nebulosity conditions and pattern ground maintenance. Moreover, for high MTF systems, MTF assessment proves to be difficult because the point spread function has a too reduced extension. Another solution consists in taking two images of the same scene, one in a high resolution mode and the other one in a lower resolution mode. When the resolution ratio is high enough (typically higher then 3), it is possible to simulate the lower resolution image through convolution with a filter and undersampling. The least square method consists in an iterative process, according to which the convolution filter evolves in order to minimize a least square criterion measuring the difference between the simulation and the low resolution image. Once the process has converged, taking the Fourier Transform of the convolution filter gives an estimation of the ratio between low resolution image MTF versus high resolution image MTF. This method may be successfully applied to remotesensing systems such as Quickbird, Ikonos, SPOT5 and future PLEIADES-HR to assess MTF in the multispectral mode. The goal of this paper is to present the MTF assessment method, the way it was validated through simulations and its application within SPOT5 context.
The detection of coal/shale interfaces close to the surface using ground penetrating radar (GPR) is difficult because the echo is drowned in unwanted signal components. These components are susceptible to changes in a...
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ISBN:
(纸本)0889864160
The detection of coal/shale interfaces close to the surface using ground penetrating radar (GPR) is difficult because the echo is drowned in unwanted signal components. These components are susceptible to changes in amplitude and cannot be removed well by standard pre-processing techniques. Second order correlation based methods such as matched filtering fail to locate the echo reliably under these conditions. Features that extract signal shape information based on the bispectrum can provide desirable immunity from clutter and noise. These features are investigated for this task using signals obtained from finite difference time domain simulations of a typical coal seam. It is shown that a patternrecognition approach using features derived from the bispectrum allows the detection of layer interfaces using GPR to be extended reliably to the near surface region.
Three-dimensional sensors based on Laser Radar (LADAR) technology possess vast potential for the future battlefield. This work presents an algorithm for the recognition of T62 and T72 tanks from 3D imagery. The algori...
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ISBN:
(纸本)0819455660
Three-dimensional sensors based on Laser Radar (LADAR) technology possess vast potential for the future battlefield. This work presents an algorithm for the recognition of T62 and T72 tanks from 3D imagery. The algorithm consists of several stages: a) Pre-processing of LADAR images to remove range noise and to determine ground level. b) Segmentation to extract regions that fulfill certain pre-defined conditions. c) Extraction of specific tank features from each region. d) Applying a Fuzzy Logic classifier applied to the feature vector to discriminate between T62 and T72 tanks and other targets or natural clutter. A commercial airborne LADAR sensor was used to acquire images from an area of 40 square kilometers with a measurement density of 20 pixels per square meter and a range noise of 15 cm (1 sigma). The images included more than a hundred man-made objects (tanks, armored personnel carriers, trucks, cranes) along with natural clutter (vegetation and boulders). Among the targets were 18 tanks, two of which were covered with a camouflage net. The algorithm recognized the 16 uncovered tanks with a False Alarm Rate (FAR) of 0.025 per square kilometer. This FAR value is better than the respective FAR values derived for 2D Imaging where Automatic Target recognition (ATR) techniques are applied. These results show promise for automatic recognition of various targets employing LADAR sensors.
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