Object detection has gained considerable interest in remotesensing community with a broad range of applications including the remote monitoring of building development in rural areas. Many earlier studies on this tas...
详细信息
ISBN:
(纸本)9781628418538
Object detection has gained considerable interest in remotesensing community with a broad range of applications including the remote monitoring of building development in rural areas. Many earlier studies on this task performed their analysis using either multispectral satellite imagery or color images obtained via an aerial vehicle. In recent years, hyperspectral imaging (HSI) has emerged as an alternative technique for remote monitoring of building developments. Unlike other imaging techniques, HSI provides a continuous spectral signature of the objects in the field of view (FOV) which facilitates the separation among different objects. In general, spectral signature similarity between objects often causes a significant amount of false alarm (FA) rate that adversely effects the overall accuracy of these systems. In order to reduce the high rate of FA posed by the pixel-wise classification, we propose a novel rural building detection method that utilizes both spatial information and spectral signature of the pixels. Proposed technique consists of three parts;a spectral signature classifier, watershed based superpixel map and an oriented-gradient filters based object detector. In our analysis, we have evaluated the performance of proposed approach using hyperspectral image dataset obtained at various elevation levels, namely 500 meters and 3000 meters. NEO HySpex VNIR-1800 camera is used for 182 band hyperspectral data acquisition. First 155 band is used due to the atmospheric effects on the last bands. Performance comparison between the proposed technique and the pixel-wise spectral classifier indicates a reduction in sensitivity rate but a notable increase in specificity and overall accuracy rates. Proposed method yields sensitivity, specificity, accuracy rate of 0.690, 0.997 and 0.992, respectively, whereas pixel-wise classification yields sensitivity, specificity, and accuracy rate of 0.758, 0.983, 0.977, respectively. Note that the sensitivity reduction is due
Satellite-based remotesensingapplications require collection of high volumes of image data of which hyperspectral images are a particular type. Hyperspectral images are collected by high-resolution instruments over ...
详细信息
ISBN:
(纸本)9788132221357;9788132221340
Satellite-based remotesensingapplications require collection of high volumes of image data of which hyperspectral images are a particular type. Hyperspectral images are collected by high-resolution instruments over a very large number of wavelengths on board a satellite/airborne vehicle and then sent onwards to a ground station for further processing. Compression of hyperspectral images is undertaken to reduce the on-board memory requirement, communication channel capacity, and the download time. Compression algorithms can be either lossless or lossy. The purpose of this paper is to review a number of compression techniques employed for onsite processing of hyperspectral image data, to reduce the transmission overhead. A review of the theory of hyperspectral images and the compression techniques employed therein with emphasis on recent research developments is presented. recent research on video compression techniques for hyperspectral imaging (HSI) is also discussed.
In recent years, developments in satellite and sensor technology brought new technologies for the assessment of the information obtained through these new sensors. One of these technologies is the Object Based image A...
详细信息
In recent years, developments in satellite and sensor technology brought new technologies for the assessment of the information obtained through these new sensors. One of these technologies is the Object Based image Analysis (OBIA) technology which allows you to make various queries on the high resolution satellite or aerial images. In this work, a damage assessment have been conducted by using object based image analysis method on a high resolution aerial image taken after a forest fire. The eCognition software which provides the object based image analysis opportunities is used in the work and the results revealed that how this software can make such flexible queries. It is possible to make various analysis on the classes obtained by the pixel based segmentation process. In this study, a small part of a large area of a high resolution aerial image is subjected to an object based analysis through the eCognition software and the size of the fire damaged area was uncovered. The analysis of the whole fire area can be obtained after applying the rule base, acquired from this process, on the whole image.
In 2012, the Workshop on Hyperspectral image and Signal processing: Evolution in remotesensing (WHISPERS), sponsored by IEEE Geoscience and remotesensing Society, moved to Shanghai, China. There were 91 oral present...
详细信息
In 2012, the Workshop on Hyperspectral image and Signal processing: Evolution in remotesensing (WHISPERS), sponsored by IEEE Geoscience and remotesensing Society, moved to Shanghai, China. There were 91 oral presentations and 31 posters. Three plenary speakers: Professor Qingxi Tong from Peking University, China, Professor Jean-Pierre Bibring from University of Paris, France, and Professor Susan Ustin from University of California, Davis, USA, introduced their cutting-edge research in this field. Following the success of this fourth WHISPERS edition, it is our great pleasure to introduce this special issue in order to present the most recentdevelopments. A large number of submissions were received, and 29 papers have been accepted after rigorous review. A few of the submissions will be published in the following issues of JSTARS, after the final reviews and revisions are completed. In the remainder of this Foreword, we briefly introduce these 29 accepted papers, which cover several important topics. In particular, 9 of these 29 papers are related to hyperspectral remotesensingapplications, which well fit the scope of the IEEE Journal of Selected Topics in Applied Earth Observations and remotesensing (JSTARS).
航空及航天遥感器的快速发展,使得多源、多时空分辨率的遥感数据成TB级增长,对海量遥感数据的高性能计算与处理提出了更高的要求。据此,当前的遥感应用已经吸收了新型硬件架构计算、集群计算和分布式计算等高性能计算领域的最新技术。本文针对高性能计算处理海量遥感数据的效率问题,分别从分布式并行遥感文件系统和高性能遥感地学计算模式两个方面来论述该问题的研究进展;在此基础上,列举了当前具有代表性的集群和分布式遥感计算平台/系统,并结合具体实验工作,详细阐述了遥感高性能计算平台gDos-IPM(Geospatial Data Operation System-imageprocessing Machine)的设计思路;最后总结了高性能遥感地学计算的发展趋势。
Connections in imageprocessing are an important notion that describes how pixels can be grouped together according to their spatial relationships and/or their gray-level values. In recent years, several works were de...
详细信息
Connections in imageprocessing are an important notion that describes how pixels can be grouped together according to their spatial relationships and/or their gray-level values. In recent years, several works were devoted to the development of new theories of connections among which hyperconnection (h-connection) is a very promising notion. This paper addresses two major issues of this theory. First, we propose a new axiomatic that ensures that every h-connection generates decompositions that are consistent for imageprocessing and, more precisely, for the design of h-connected filters. Second, we develop a general framework to represent the decomposition of an image into h-connections as a tree that corresponds to the generalization of the connected component tree. Such trees are indeed an efficient and intuitive way to design attribute filters or to perform detection tasks based on qualitative or quantitative attributes. These theoretical developments are applied to a particular fuzzy h-connection, and we test this new framework on several classical applications in imageprocessing, i.e., segmentation, connected filtering, and document image binarization. The experiments confirm the suitability of the proposed approach: It is robust to noise, and it provides an efficient framework to design selective filters.
Field spectroradiometers are widely used for environmental applications where data describing visible and near-infrared reflectance factors are of interest. recentdevelopments in spaceborne and airborne instruments w...
详细信息
Field spectroradiometers are widely used for environmental applications where data describing visible and near-infrared reflectance factors are of interest. recentdevelopments in spaceborne and airborne instruments with multiple view angle (MVA) capabilities have resulted in a demand for ground measurements to support these missions. Lightweight portable spectroradiometers offer an appropriate means of collecting MVA spectral reflectance factor data because they are more easily manoeuvrable than other spectroradiometers, but their physical capabilities have not yet been explored in this context. This letter presents the results of a focused experiment aimed at evaluating the field capabilities of a miniaturized Ocean Optics instrument in MVA settings for soil surface roughness applications. MVA hemispherical-conical reflectance factors were collected in situ from soil surfaces whose roughness was determined using a laser profiling survey. The results showed a significant negative relationship (R(2) = 0.74;p < 0.01) between directional reflectance factors measured at 870 nm in the forward-scattering region and a soil structural measure derived from laser profiling data. This corroborates the results of other published studies and suggests that Ocean Optics instruments can be used to support hyperspectral MVA investigations.
New developments in small spacecraft capabilities will soon enable formation-flying constellations of small satellites, performing cooperative distributed remotesensing at a fraction of the cost of traditional large ...
详细信息
ISBN:
(纸本)9780819492777
New developments in small spacecraft capabilities will soon enable formation-flying constellations of small satellites, performing cooperative distributed remotesensing at a fraction of the cost of traditional large spacecraft missions. As part of ongoing research into applications of formation-flight technology, recent work has developed a mission concept based on combining synthetic aperture radar (SAR) with automatic identification system (AIS) data. Two or more microsatellites would trail a large SAR transmitter in orbit, each carrying a SAR receiver antenna and one carrying an AIS antenna. Spaceborne AIS can receive and decode AIS data from a large area, but accurate decoding is limited in high traffic areas, and the technology relies on voluntary vessel compliance. Furthermore, vessel detection amidst speckle in SAR imagery can be challenging. In this constellation, AIS broadcasts of position and velocity are received and decoded, and used in combination with SAR observations to form a more complete picture of maritime traffic and identify potentially non-cooperative vessels. Due to the limited transmit power and ground station downlink time of the microsatellite platform, data will be processed onboard the spacecraft. Herein we present the onboard data processing portion of the mission concept, including methods for automated SAR image registration, vessel detection, and fusion with AIS data. Georeferencing in combination with a spatial frequency domain method is used for image registration. Wavelet-based speckle reduction facilitates vessel detection using a standard CFAR algorithm, while leaving sufficient detail for registration of the filtered and compressed imagery. Moving targets appear displaced from their actual position in SAR imagery, depending on their velocity and the image acquisition geometry;multiple SAR images acquired from different locations are used to determine the actual positions of these targets. Finally, a probabilistic inference mode
This Special Issue seeks to review progress in synthetic aperture radar imaging which has been made possible through new algorithms and enabling hardware. It serves to capture the approaches propelling recent cutting-...
This Special Issue seeks to review progress in synthetic aperture radar imaging which has been made possible through new algorithms and enabling hardware. It serves to capture the approaches propelling recent cutting-edge research and scholarly activities in SAR imagery. SAR has become a valuable tool for civilian remotesensingapplications as well as for military surveillance and reconnaissance. SAR operations can take place in all weather and times. SAR data can provide key information about the scene which can be extracted e.g. from the polarimetric features, the phase variation over time, and the reflectivity dependency on frequency. A wide variety of air- and space based sensors for long and short range operation has been realized, operating at frequencies extending from VHF to the upper millimeter wave region. Spectacular missions I ike the Shuttle Radar Topographic Mission, the TanDEM-X satellite pair and the COSMO/SkyMed constellation have underscored the unique and important role of SAR. In addition to the basic SAR modes, across- and along track interferometry have been established. Multi-band operations and the full polarimetric scattering matrix have been effectively utilized. We encourage paper submissions that highlight recent trends and applications of SAR imaging. We welcome contributions showing the marked improvements in SAR imaging and the attributes of efficient data acquisition, fast image computations, high image resolution, and effective image segmentations. This Special Issue aims to present the new developments in radar imaging related to polarimetry, bi- and multi-static sensors including MIMO architectures, novel focusing techniques and algorithms, compressive sensing and sparse imaging reconstructions, and other forthcoming radar imaging techniques. Air- and spaceborne SAR systems and techniques will also be considered.
暂无评论