The urban fringe which can he seen as a special form of regional ecosystems with a spatial structure gradually from Urban to rural areas of transition, has strong heterogeneity and is typical of ecologically sensitive...
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ISBN:
(纸本)9781441902085
The urban fringe which can he seen as a special form of regional ecosystems with a spatial structure gradually from Urban to rural areas of transition, has strong heterogeneity and is typical of ecologically sensitive areas. The expansion of city caused wide attention to the landscape effect of the changes. With the help of GIS, we got landscape pattern changes before and after town planning of Gaoliying town in Beijing by using high resolution image and large-scale map. The results showed that landscape shape index, contagion index and Simpson evenness index increased while landscape diversity index reduced. The pattern of reasonable land use would improve and landscape pattern come to perfect. The intensity index of human disturbance increased. Comparing three increase modes of town development, the landscape pattern change of Gaoliying town is peripheral increase mode.
In this paper, we introduce a variational framework towards automatic 3D building reconstruction from optical and Lidar data. Multiple 3D competing building priors are considered under a recognition-driven way. These ...
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ISBN:
(纸本)9781424456536;9781424456543
In this paper, we introduce a variational framework towards automatic 3D building reconstruction from optical and Lidar data. Multiple 3D competing building priors are considered under a recognition-driven way. These models, under a certain hierarchical representation, describe the space of solutions and under a fruitful synergy with an inferential procedure recover the observed scene's geometry. Our formulation allows the cue with the higher spatial resolution to constrain properly the boundaries detection procedure ensuring, in this way, optimal results in terms of accuracy. Such an integrated approach is defined in a variational context, solves segmentation in both spaces, addresses fusion in a natural manner and allows multiple competing priors to determine the pose and 3D geometry from the observed data. Very promising experimental results demonstrate the potentials of our approach.
Obtaining training sets for special hyperspectral data sets or applications seems so time consuming and expensive especially for relatively inaccessible locations. Moreover, current techniques of imageprocessing and ...
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Obtaining training sets for special hyperspectral data sets or applications seems so time consuming and expensive especially for relatively inaccessible locations. Moreover, current techniques of imageprocessing and patternrecognition are not robust enough to make automated remotesensing interpretation feasible. The margin infused relaxed algorithm (MIRA) is a new perceptron-like online algorithm with a margin-dependent learning rate; meanwhile, it's also a specific online algorithm that seeks a set of prototypes to represent each class. In this paper, we put emphasis on building an online framework by MIRA, which can naturally combine inputs from human and learn as few labeled data points as possible. Experimental results have proved that the MIRA applied in our method is effective in classification problem and economical of the computation time cost.
Shadow detection in high spatial resolution remotesensingimage is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm i...
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Shadow detection in high spatial resolution remotesensingimage is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm in the Hue-Saturation-Intensity (HSI) color space. Because the pixel matrix is a large-scale matrix, if we apply AP algorithm directly on the raw pixel space, it will be computation intensive to calculate the similarity matrix. To solve this problem, we propose to divide the matrix into several blocks and then applying AP to detect shadows in H, S and I components respectively. Then, three detected images are fused to obtain a final shadow detection result. Comparative experiments are performed for K-means and threshold segmentation methods. The experimental results show that higher detection accuracy of the proposed approach is obtained, and it can solve the problems of false dismissals of K-means and threshold segmentation method.
Classification and extraction of geospatial features from high spatial resolution imageries approved is one of the most significant steps for spatial database acquisition and updating in GIS. This research is to explo...
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ISBN:
(纸本)9781424445622
Classification and extraction of geospatial features from high spatial resolution imageries approved is one of the most significant steps for spatial database acquisition and updating in GIS. This research is to explore the methodologies of recognizing shape and elevation characteristics of spatial features on the remote sensed images. We focus on the road network classification and extraction among various features on the ground because it carries unique characteristic of elongation. We combined both a patternrecognition model of connected component labeling (CCL) in two dimensional imageprocessing, and a three dimensional DEM elevation filtering model to extract the road and street features from high resolution imageries. Samples of digital aerial photographs in Erie County, New York were used to test the methodology. The results indicated that the correctness of road extraction in rural areas can reach 69.1%; that of completeness is 74.9%; and the overall quality is 73.1%. By contrast, the correctness in urban high-rise region is only 39.5%; that of completeness is 42.8%; and the overall quality is 32.8%.
A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Fe...
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ISBN:
(纸本)9781424449934
A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA.
A feature extraction method from remotesensingimages obtain by cameras by light polarization and extraction of the of several frequencies of light instead of just (R, G, B). The number of frequency bands varies from...
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ISBN:
(纸本)1601320787
A feature extraction method from remotesensingimages obtain by cameras by light polarization and extraction of the of several frequencies of light instead of just (R, G, B). The number of frequency bands varies from eight in some cameras to over fifty in others. These are specialized cameras used by JPL, NASA, Universities, and other research organizations The cameras could be mounted on an airplane, a helicopter, low Earth orbit satellite (LEO), medium Earth orbit (MEO), etc. The camera provides information of more than three channels, we extract a number of features and create a classifier to understand if there a forest fire hidden, if there is smoke, pollution in the air, etc. the features we use are spatial, temporal, frequency domain features, wavelet domain and features in the discrete cosine transform space.
Extracting target information from the remotesensingimages has been becoming an important method of updating the spatial geography data. With the development of spatial technology, sensor technology, digital image p...
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remotesensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seas...
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ISBN:
(纸本)1601320787
remotesensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training image pairs. The proposed method first generates a vegetation map for pixels corresponding to vegetative areas, using ISODATA clustering, morphological operations and vegetation classification. It then generates seasonal color adaptation of a target input image based on a pair of training images, which depict the same area but were captured in different seasons, using image analogies technique. The vegetation map ensures that only the colors of vegetative areas in the target image are altered and also improves the performance of the original image analogies technique. The proposed method can be used in flight simulations and other applications.
The proceedings contain 75 papers. The topics discussed include: enhancement of skin tilt pattern for lesion classification;wavelet de-noising and gradient enhancement in biomedical imageprocessing;transdermal measur...
ISBN:
(纸本)9780889867598
The proceedings contain 75 papers. The topics discussed include: enhancement of skin tilt pattern for lesion classification;wavelet de-noising and gradient enhancement in biomedical imageprocessing;transdermal measurement of red blood cell motion in superficial capillaries;multiple watermark embedding and blind extraction scheme in wavelet-spatial domains based on ROI;tissue recognition on pressure ulcer images in non controlled environments;ophthalmologic image registration based on shape-context: application to fundus autofluorescence (FAF) images;plane detection from monocular image sequences;algorithm for stitching of video sequences;measuring railroad wheel profiles through imageprocessing technology;object detection using Gabor responses and texture information in low contrast infrared images;and a hybrid method for segmentation of multispectral remotesensingimages.
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