scholarly journals Influence of the System MTF on the On-Board Lossless Compression of Hyperspectral Raw Data

2019 ◽  
Vol 11 (7) ◽  
pp. 791 ◽  
Author(s):  
Bruno Aiazzi ◽  
Massimo Selva ◽  
Alberto Arienzo ◽  
Stefano Baronti
Keyword(s):  
Spatial Resolution ◽  
Imaging System ◽  
Lossless Compression ◽  
Hyperspectral Data ◽  
Data Systems ◽  
Mass Storage ◽  
Modulation Transfer ◽  
Time Data ◽  
Space Data ◽  
The Impact

A noticeable topic to be pursued in the field of on-board real-time data processing is the influence of the modulation transfer function (MTF) of the image acquisition system on the lossless compressibility of raw (that is, uncalibrated) hyperspectral data. Actually, notwithstanding the system device is constrained by several design and manufacturing requirements, the impact of the on-board MTF on the performance of data compressors is becoming remarkable. In particular, the aim of reducing both transmission bandwidth/power and mass storage can be efficiently pursued. Such an analysis is expected to be useful especially for systems employed in mini-satellites, whose payload must be compact and light. From this perspective, this paper investigates the performance of a typical imaging system that acquires low/medium-spatial-resolution images, by considering high-resolution reference data, which simulate the real scene to be imaged. To this end, standard Consultative Committee for Space Data Systems (CCSDS) Aviris 2006 data have been chosen, due to their spatial resolution of 17 m, which is adequate to be a reference for simulated data whose spatial resolution is foreseen between 50 and 150 m. MTF requirements are usually provided based on the cut-off value of the amplitude at the Nyquist frequency, which is defined as a half of the sampling frequency. Typically, a cut-off value between 0 . 2 and 0 . 3 ensures that a sufficient amount of information is delivered from the scene to the acquired image, by avoiding at the same time the degradation due to an excessive aliasing distortion. All the scores are achieved by running the standard lossless compression scheme CCSDS 1.2.3.0-B-1 for multispectral/hyperspectral data, as a function of the cut-off value and different noise acquisition levels. The final results, and related plots, show that this analysis can suggest a suitable choice for the cut-off value, to ensure both a sufficient quality and low bit rates for the transmitted data to the ground station.

scholarly journals Fusing China GF-5 Hyperspectral Data with GF-1, GF-2 and Sentinel-2A Multispectral Data: Which Methods Should Be Used?

2020 ◽  
Vol 12 (5) ◽  
pp. 882 ◽  
Author(s):  
Kai Ren ◽  
Weiwei Sun ◽  
Xiangchao Meng ◽  
Gang Yang ◽  
Qian Du
Keyword(s):  
Spatial Resolution ◽  
Comprehensive Evaluation ◽  
Evaluation Study ◽  
Hyperspectral Data ◽  
Modulation Transfer ◽  
Multispectral Data ◽  
Spectral Bands ◽  
Spectral Fidelity ◽  
Fusion Methods ◽  
Sentinel 2A

The China GaoFen-5 (GF-5) satellite sensor, which was launched in 2018, collects hyperspectral data with 330 spectral bands, a 30 m spatial resolution, and 60 km swath width. Its competitive advantages compared to other on-orbit or planned sensors are its number of bands, spectral resolution, and swath width. Unfortunately, its applications may be undermined by its relatively low spatial resolution. Therefore, the data fusion of GF-5 with high spatial resolution multispectral data is required to further enhance its spatial resolution while preserving its spectral fidelity. This paper conducted a comprehensive evaluation study of fusing GF-5 hyperspectral data with three typical multispectral data sources (i.e., GF-1, GF-2 and Sentinel-2A (S2A)), based on quantitative metrics, classification accuracy, and computational efficiency. Datasets on three study areas of China were utilized to design numerous experiments, and the performances of nine state-of-the-art fusion methods were compared. Experimental results show that LANARAS (this method was proposed by lanaras et al.), Adaptive Gram–Schmidt (GSA), and modulation transfer function (MTF)-generalized Laplacian pyramid (GLP) methods are more suitable for fusing GF-5 with GF-1 data, MTF-GLP and GSA methods are recommended for fusing GF-5 with GF-2 data, and GSA and smoothing filtered-based intensity modulation (SFIM) can be used to fuse GF-5 with S2A data.

scholarly journals Application of airborne hyperspectral data to mineral exploration in North-East Greenland

1969 ◽  
Vol 20 ◽  
pp. 71-74 ◽  
Author(s):  
Tapani Tukiainen ◽  
Bjørn Thomassen
Keyword(s):  
Spectral Analysis ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Wavelength Range ◽  
Imaging System ◽  
Mineral Exploration ◽  
Hyperspectral Data ◽  
East Greenland ◽  
North East ◽  
Arctic Conditions

An airborne hyperspectral survey was organised by the Geological Survey of Denmark and Greenland (GEUS) and carried out in 2000 to test the use of spectral analysis in mineral exploration under Arctic conditions. The hyperspectral data were acquired by using the HyMap imaging system consisting of sensors that collect reflected solar radiation in 126 bands covering the 440–2500 nm wavelength range (Bedini & Tukiainen 2008). The spatial resolution was 4 × 4 m (Tukiainen 2001). Eight sites underlain by Caledonian or post-Caledonian rocks with known mineral occurrences (Fig. 1) were tested. The project was financially supported by the Greenland Bureau of Minerals and Petroleum and the data were analysed by GEUS. Here we provide a summary of the results.

Monitoring the state of waste disposal facilities using remote sensing data

2018 ◽  
Vol 941 (11) ◽  
pp. 47-53
Author(s):  
U.D. Niyazgulov ◽  
A.A. Gebgart ◽  
V.G. Krestinkov ◽  
F.K. Niyazgulov
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Aerial Survey ◽  
The State ◽  
Household Waste ◽  
Ecological State ◽  
Solid Waste Landfills ◽  
The Impact

The technology of monitoring objects of solid household waste in the Moscow region using the data of space and aerial survey is considered. In order to solve the problem, we used space survey materials obtained from the Worldview-2 satellite (spatial resolution of 1,5 m per pixel) and special aerial filming performed with the help of an Azimuth-2M photo-imaging system based on a hang glider (spatial resolution not coarser than 0,1 m per pixel). On the basis of those materials, digital models of accommodation facilities for solid household wastes and orthophotoplans were obtained, using which a comparative analysis of the state of landfills was performed. The analysis was carried out according to several indicators, including the impact of polygons on the ecological state of the surrounding territories and the cluttering the surrounding territory with waste was determined. It is shown that the use of remote sensing materials enables obtaining the necessary information to monitor the state of solid waste landfills, while performing the minimum amount of field geodetic works.

scholarly journals DETECTION AND QUANTIFICATION OF INDUSTRIAL METHANE PLUME WITH THE AIRBORNE HYSPEX-NEO CAMERA AND APPLICATIONS TO SATELLITE DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 821-827
Author(s):  
N. Nesme ◽  
P.-Y. Foucher ◽  
S. Doz
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Hyperspectral Data ◽  
Flight Altitude ◽  
Artificial Data ◽  
Infrared Spectrometer ◽  
The Impact ◽  
Detection And Quantification

Abstract. The control and monitoring of greenhouse gases is an important issue for the study of climate change, for the impact in terms of public health or for the risks related to industry. An algorithm has been developped dedicated to commercial airborne hyperspectral camera as HySpex-NEO for the detection of industrial methane plume and the quantification of the emission source. HySpex-NEO is an imager used in airborne campaign with a spatial resolution of 1.4 m at flight altitude of 2 km, a swath of 650 m and a spectral resolution of 6 nm. This algorithm has been validated over a controlled release less than 100 g/s during an airborne campaign over Lacq (France) industry. It has also been applied to the Aliso Canyon leakage data acquired with AVIRIS JPL (Airborne Visible Infrared Spectrometer) with a spatial resolution of 6.8 m at flight altitude of 6 km, a swath of 5.6 km and a spectral resolution of 10 nm. Application to satellite hyperspectral data is shown on artificial data derived from airborne hyperspectral acquisitions.

scholarly journals ACCOUNTING FOR VARIANCE IN HYPERSPECTRAL DATA COMING FROM LIMITATIONS OF THE IMAGING SYSTEM

2016 ◽  
Vol XLI-B7 ◽  
pp. 365-369
Author(s):  
B. Shurygin ◽  
M. Shestakova ◽  
A. Nikolenko ◽  
E. Badasen ◽  
P. Strakhov
Keyword(s):  
Hyperspectral Image ◽  
Imaging System ◽  
A Priori ◽  
Gaussian Model ◽  
Projection Pursuit ◽  
Hyperspectral Data ◽  
Detector Response ◽  
Large Set ◽  
Calibration Data ◽  
The Impact

Over the course of the past few years, a number of methods was developed to incorporate hyperspectral imaging specifics into generic data mining techniques, traditionally used for hyperspectral data processing. Projection pursuit methods embody the largest class of methods empoyed for hyperspectral image data reduction, however, they all have certain drawbacks making them either hard to use or inefficient. It has been shown that hyperspectral image (HSI) statistics tend to display “heavy tails” (Manolakis2003)(Theiler2005), rendering most of the projection pursuit methods hard to use. Taking into consideration the magnitude of described deviations of observed data PDFs from normal distribution, it is apparent that <i>a priori</i> knowledge of variance in data caused by the imaging system is to be employed in order to efficiently classify objects on HSIs (Kerr, 2015), especially in cases of wildly varying SNR. A number of attempts to describe this variance and compensating techniques has been made (Aiazzi2006), however, new data quality standards are not yet set and accounting for the detector response is made under large set of assumptions. Current paper addresses the issue of hyperspectral image classification in the context of different variance sources based on the knowledge of calibration curves (both spectral and radiometric) obtained for each pixel of imaging camera. A camera produced by ZAO NPO Lepton (Russia) was calibrated and used to obtain a test image. <i>A priori</i> known values of SNR and spectral channel cross-correlation were incorporated into calculating test statistics used in dimensionality reduction and feature extraction. Expectation-Maximization classification algorithm modification for non-Gaussian model as described by (Veracini2010) was further employed. The impact of calibration data coarsening by ignoring non-uniformities on false alarm rate was studied. Case study shows both regions of scene-dominated variance and sensor-dominated variance, leading to different preprocession parameters and, ultimatively, classification results. A multilevel system for denoting hyperspectral pushbroom scanners calibration quality was proposed.

scholarly journals ACCOUNTING FOR VARIANCE IN HYPERSPECTRAL DATA COMING FROM LIMITATIONS OF THE IMAGING SYSTEM

2016 ◽  
Vol XLI-B7 ◽  
pp. 365-369
Author(s):  
B. Shurygin ◽  
M. Shestakova ◽  
A. Nikolenko ◽  
E. Badasen ◽  
P. Strakhov
Keyword(s):  
Hyperspectral Image ◽  
Imaging System ◽  
A Priori ◽  
Gaussian Model ◽  
Projection Pursuit ◽  
Hyperspectral Data ◽  
Detector Response ◽  
Large Set ◽  
Calibration Data ◽  
The Impact

Over the course of the past few years, a number of methods was developed to incorporate hyperspectral imaging specifics into generic data mining techniques, traditionally used for hyperspectral data processing. Projection pursuit methods embody the largest class of methods empoyed for hyperspectral image data reduction, however, they all have certain drawbacks making them either hard to use or inefficient. It has been shown that hyperspectral image (HSI) statistics tend to display “heavy tails” (Manolakis2003)(Theiler2005), rendering most of the projection pursuit methods hard to use. Taking into consideration the magnitude of described deviations of observed data PDFs from normal distribution, it is apparent that &lt;i&gt;a priori&lt;/i&gt; knowledge of variance in data caused by the imaging system is to be employed in order to efficiently classify objects on HSIs (Kerr, 2015), especially in cases of wildly varying SNR. A number of attempts to describe this variance and compensating techniques has been made (Aiazzi2006), however, new data quality standards are not yet set and accounting for the detector response is made under large set of assumptions. Current paper addresses the issue of hyperspectral image classification in the context of different variance sources based on the knowledge of calibration curves (both spectral and radiometric) obtained for each pixel of imaging camera. A camera produced by ZAO NPO Lepton (Russia) was calibrated and used to obtain a test image. &lt;i&gt;A priori&lt;/i&gt; known values of SNR and spectral channel cross-correlation were incorporated into calculating test statistics used in dimensionality reduction and feature extraction. Expectation-Maximization classification algorithm modification for non-Gaussian model as described by (Veracini2010) was further employed. The impact of calibration data coarsening by ignoring non-uniformities on false alarm rate was studied. Case study shows both regions of scene-dominated variance and sensor-dominated variance, leading to different preprocession parameters and, ultimatively, classification results. A multilevel system for denoting hyperspectral pushbroom scanners calibration quality was proposed.

scholarly journals Reliability Analysis of the SHyLoC CCSDS123 IP Core for Lossless Hyperspectral Image Compression Using COTS FPGAs

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1681
Author(s):  
Luis Alberto Aranda ◽  
Antonio Sánchez ◽  
Francisco Garcia-Herrero ◽  
Yubal Barrios ◽  
Roberto Sarmiento ◽  
...  
Keyword(s):  
Image Compression ◽  
Reliability Analysis ◽  
Hyperspectral Image ◽  
European Space Agency ◽  
Lossless Compression ◽  
Data Systems ◽  
Ip Core ◽  
Space Applications ◽  
Space Data ◽  
Hyperspectral Image Compression

Hyperspectral images can comprise hundreds of spectral bands, which means that they can represent a large volume of data difficult to manage with the available on-board resources. Lossless compression solutions are interesting for reducing the amount of information stored or transmitted while preserving it at the same time. The Hyperspectral Lossless Compressor for space applications (SHyLoC), which is part of the European Space Agency (ESA) IP core’s library, has been demonstrated to meet the requirements of space missions in terms of compression efficiency, low complexity and high throughput. Currently, there is a trend to use Commercial Off-The-Shelf (COTS) on-board electronic devices on small satellites. Moreover, commercial Field-Programmable Gate Arrays (FPGAs) have been used in a number of them. Hence, a reliability analysis is required to ensure the robustness of the applications to Single Event Upsets (SEUs) in the configuration memory. In this work, we present a reliability analysis of this hyperspectral image compression module as a first step towards the development of ad-hoc fault-tolerant protection techniques for the SHyLoC IP core. The reliability analysis is performed using a fault-injection-based experimental set-up in which a hardware implementation of the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-1 lossless compression standard is tested against configuration memory errors in a Xilinx Zynq XC7Z020 System-on-Chip. The results obtained for unhardened and redundancy-based protected versions of the module are put into perspective in terms of area/power consumption and availability/protection coverage gained to provide insight into the development of more efficient knowledge-based protection schemes.

scholarly journals Modulation transfer function evaluation of cone beam computed and microcomputed tomography by using slanted edge phantom

2019 ◽  
Author(s):  
Szabó TAMÁS BENCE
Keyword(s):  
Transfer Function ◽  
Spatial Resolution ◽  
Modulation Transfer Function ◽  
Imaging System ◽  
Ct Images ◽  
Function Evaluation ◽  
Strong Positive Correlation ◽  
Micro Ct ◽  
Modulation Transfer ◽  
Voxel Size

Modulation transfer function (MTF) is a well known and widely accepted method for evaluating the spatial resolution of a digital radiographic imaging system. In the present study our aim was to evaluate the MTF obtained from CBCT and micro-CT images. A cylinder shaped phantom designed for slanted-edge method was scanned by a CBCT device at a 100 µm isometric voxel size and by a micro-CT device at a 20 µm isometric voxel size, simultaneously. The MTF curves were calculated and the mean spatial resolutions at 10% MTF were 3.33 + 0.29 lp/mm in the case of CBCT images and 13.35 + 2.47 lp/mm in the case of micro-CT images. The values showed a strong positive correlation regarding the CBCT and the micro-CT spatial resolution values, respectively. Our results suggests that CBCT imaging devices with a voxel size of 100 µm or below might aid the validation of fine anatomical structures and allowing the opportunity for reliable micromorphometric examinations

Microscopic Three-Dimensional Imaging Theory Based on RIKES

2007 ◽  
Vol 364-366 ◽  
pp. 1089-1094
Author(s):  
Li Na Guo ◽  
Zhi Lie Tang ◽  
Da Xing
Keyword(s):  
Spatial Resolution ◽  
Kerr Effect ◽  
Imaging System ◽  
Three Dimensional ◽  
Microscopic Imaging ◽  
Two Photon ◽  
Imaging Theory ◽  
Imaging Properties ◽  
The Impact

A novel nonlinear confocal microscopic imaging system based on Raman induced Kerr effect spectroscopy (RIKES) is presented in this paper. The three-dimensional (3-D) microscopic imaging theory is derived with the Fourier imaging theory and nonlinear optical principle. The impact of RIKES on the spatial resolution and imaging properties of confocal microscopic imaging system has been analyzed in detail by the imaging theory. It’s proved that the RIKES nonlinear microscopic imaging system can effectively improve the imaging contrast and provide more characteristic information on Raman spectrum and optical nonlinear Kerr effect, thus greatly improving the imaging quality of confocal microscopic imaging system. It’s shown that the spatial resolution of RIKES confocal microscopic imaging system is higher than that of two-photon confocal microscopic imaging system.

scholarly journals Spatial Distortion Assessments of a Low-Cost Laboratory and Field Hyperspectral Imaging System

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4267
Author(s):  
Andrija Krtalić ◽  
Vanja Miljković ◽  
Dubravko Gajski ◽  
Ivan Racetin
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Low Cost ◽  
Ccd Camera ◽  
Hyperspectral Data ◽  
Modulation Transfer ◽  
Spatial Distortion ◽  
Visible Part ◽  
Spatial Calibration

This article describes the adaptation of an existing aerial hyperspectral imaging system in a low-cost setup for collecting hyperspectral data in laboratory and field environment and spatial distortion assessments. The imaging spectrometer system consists of an ImSpector V9 hyperspectral pushbroom scanner, PixelFly high performance digital CCD camera, and a subsystem for navigation, position determination and orientation of the system in space, a sensor bracket and control system. The main objective of the paper is to present the system, with all its limitations, and a spatial calibration method. The results of spatial calibration and calculation of modulation transfer function (MTF) are reported along with examples of images collected and potential uses in agronomy. The distortion value rises drastically at the edges of the image in the near-infrared segment, while the results of MTF calculation showed that the image sharpness was equal for the bands from the visible part of the spectrum, and approached Nyquist’s theory of digitalization. In the near-infrared part of the spectrum, the MTF values showed a less sharp decrease in comparison with the visible part. Preliminary image acquisition indicates that this hyperspectral system has potential in agronomic applications.

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