0000000001056329
AUTHOR
J. Calpe
Semi-Supervised Classification Method for Hyperspectral Remote Sensing Images
A new approach to the classification of hyperspectral images is proposed. The main problem with supervised methods is that the learning process heavily depends on the quality of the training data set. In remote sensing, the training set is useful only for simultaneous images or for images with the same classes taken under the same conditions; and, even worse, the training set is frequently not available. On the other hand, unsupervised methods are not sensitive to the number of labelled samples since they work on the whole image. Nevertheless, relationship between clusters and classes is not ensured. In this context, we propose a combined strategy of supervised and unsupervised learning met…
Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data
In addition to typical random noise, remote sensing hyperspectral images are generally affected by non-periodic partially deterministic disturbance patterns due to the image formation process and characterized by a high degree of spatial and spectral coherence. This paper presents a new technique that faces the problem of removing the spatial coherent noise known as vertical stripping (VS) usually found in images acquired by push-broom sensors, in particular for the Compact High Resolution Imaging Spectrometer (CHRIS). The correction is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. The proposed method introduces a way to…
Urban monitoring using multi-temporal SAR and multi-spectral data
In some key operational domains, the joint use of synthetic aperture radar (SAR) and multi-spectral sensors has shown to be a powerful tool for Earth observation. In this paper, we analyze the potentialities of combining interferometric SAR and multi-spectral data for urban area characterization and monitoring. This study is carried out following a standard multi-source processing chain. First, a pre-processing stage is performed taking into account the underlying physics, geometry, and statistical models for the data from each sensor. Second, two different methodologies, one for supervised and another for unsupervised approaches, are followed to obtain features that optimize the urban rela…
Robust adaptive algorithm with low computational cost
An adaptive algorithm, which is robust to impulsive noise, is proposed. The cost function underlying this algorithm contains a parameter that controls the immunity to impulsive noise and can be easily adapted. Moreover, weight updating involves a nonlinear function, which recently has been shown to have an efficient hardware implementation. The proposed adaptive algorithm has been successfully tested in terms of accuracy and convergence on a system-identification simulation.
Evaluation of remote sensing of vegetation fluorescence by the analysis of diurnal cycles
Chlorophyll fluorescence (ChF) emission is a direct indicator of the photosynthetic activity of vegetation, which is a key parameter of the carbon cycle. This paper analyses chlorophyll fluorescence evolution at leaf level during a complete diurnal cycle in simulated and natural conditions, for two species under different stress conditions. Absolute spectral radiance of the ChF emission is obtained allowing a quantitative derivation of the fluorescence yield of the ChF, which correlates well with established fluorescence instruments. The studied cases show that the ChF emission is mainly driven by the photosynthetic active radiation during the whole cycle, but the fluorescence yield is seve…
Sensitivity analysis of the fraunhofer line discrimination method for the measurement of chlorophyll fluorescence using a field spectroradiometer
The Fraunhofer Line Discrimination (FLD) principle is established as a good method for remote sensing of solar induced chlorophyll fluorescence. Some improvements to the method are analysed in order to determine and reduce the sources of error in the estimation of the fluorescence emission. A sensitivity analysis has been performed over simulated data generated from real diurnal cycle measurements.
Cloud screening with combined MERIS and AATSR images
This paper presents a cloud screening algorithm based on ensemble methods that exploits the combined information from both MERIS and AATSR instruments on board ENVISAT in order to improve current cloud masking products for both sensors. The first step is to analyze the synergistic use of MERIS and AATSR images in order to extract some physically-based features increasing the separability of clouds and surface. Then, several artificial neural networks are trained using different sets of input features and different sets of training samples depending on acquisition and surface conditions. Finally, outputs of the trained neural networks are combined at the decision level to construct a more ac…
Toll-quality digital secraphone
This paper describes the design and performance of a secraphone that, when plugged between any conventional telephone set and the public telephone network, protects the speech information travelling through the PSTN. The device has a transparent operating mode that does not alter the signal and a secure mode, accessed upon request of any of the speakers, that encrypts the speech with digital techniques, assuring privacy against unwanted listeners. At the transmission branch, voice is sampled, coded with a CELP scheme at 9600 bps (with a slow mode at 7200 bps), encrypted with a proprietary algorithm and interfaced to the line with a V.32 modem chip set. The keys for encryption are establishe…
A Novel Approach to Introducing Adaptive Filters Based on the LMS Algorithm and Its Variants
This paper presents a new approach to introducing adaptive filters based on the least-mean-square (LMS) algorithm and its variants in an undergraduate course on digital signal processing. Unlike other filters currently taught to undergraduate students, these filters are nonlinear and time variant. This proposal introduces adaptive filtering in the context of a linear time-invariant system using a real problem. In this way, introducing adaptive filters using concepts already familiar to the students motivates their interest through practical application. The key point for this simplification is that the input to the filter is constant so that the adaptive filter becomes linear. Therefore, a …
ETAT: Expository Text Analysis Tool.
Qualitative methods that analyze the coherence of expository texts not only are time consuming, but also present challenges in collecting data on coding reliability. We describe software that analyzes expository texts more rapidly and produces a notable level of objectivity. ETAT (Expository Text Analysis Tool) analyzes the coherence of expository texts. ETAT adopts a symbolic representational system, known as conceptual graph structures. ETAT follows three steps: segmentation of a text into nodes, classification of the unidentified nodes, and linking the nodes with relational arcs. ETAT automatically constructs a graph in the form of nodes and their interrelationships, along with various a…
SmartSpectra: Applying multispectral imaging to industrial environments
SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …
High performance hardware correlation coefficient assessment using programmable logic for ECG signals
Abstract Correlation coefficient is frequently used to obtain cardiac rhythm by peak estimation and appreciate differences in the signal compared to a pattern. This work focuses on the description of a real-time correlation assessment procedure. Applied to electrocardiogram (ECG) signals, a new correlation value is obtained every new sample and pulse detection information is provided. The ECG pattern is internally stored and can be changed when desired. This procedure is useful in Systems on Chip implementation and can be applied to design compact ECG monitoring systems consisting on a system on chip where programmable logic offloads the main processor. A Xilinx FPGA device has been used fo…
Study of the diurnal cycle of stressed vegetation for the improvement of fluorescence remote sensing
Chlorophyll fluorescence (Chf) emission allows estimating the photosynthetic activity of vegetation - a key parameter for the carbon cycle models - in a quite direct way. However, measuring Chf is difficult because it represents a small fraction of the radiance to be measured by the sensor. This paper analyzes the relationship between the solar induced Chf emission and the photosynthetically active radiation (PAR) in plants under water stress condition. The solar induced fluorescence emission is measured at leaf level by means of three different methodologies. Firstly, an active modulated light fluorometer gives the relative fluorescence yield. Secondly, a quantitative measurement of the Ch…
Remote sensing of chlorophyll fluorescence for estimation of stress in vegetation. Recommendations for future missions
Vegetation monitoring is a key issue in Earth Observation due to its relation with the global CO2 cycle. Chlorophyll fluorescence (ChF) emitted by the vegetation is an accurate indicator of the plant status and their photosynthetic activity. This work analyses the diurnal evolution of the ChF emission spectrum and the fluorescence yield in order to determine the best conditions for remote sensing of ChF from a satellite platform. The ChF evolution is studied at leaf level during several diurnal cycles, in simulated conditions, for two species under different stress conditions. The analysis of the signal levels gives an estimation of the values of ChF emission which could be observed from a …
Cloud screening and multitemporal unmixing of MERIS FR data
The operational use of MERIS images can be hampered by the presence of clouds. This work presents a cloud screening algorithm that takes advantage of the high spectral and radiometric resolutions of MERIS and the specific location of some of its bands to increase the cloud detection accuracy. Moreover, the proposed algorithm provides a per-pixel probabilistic map of cloud abundance rather than a binary cloud presence flag. In order to test the proposed algorithm we propose a cloud screening validation method based on temporal series. In addition, we evaluate the impact of the cloud screening in a multitemporal unmixing application, where a temporal series of MERIS FR images acquired over Th…
Cloud detection for CHRIS/Proba hyperspectral images
Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant source of error in both sea and land cover biophysical parameter retrieval. Sensors with spectral channels beyond 1 um have demonstrated good capabilities to perform cloud masking. This spectral range can not be exploited by recently developed hyperspectral sensors that work in the spectral range between 400- 1000 nm. However, one can take advantage of their high number of channels and spectral resolution to increase the cloud detection accuracy, and to describe properly the detected c…
Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images
Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, whi…