Showing papers in "IEEE Geoscience and Remote Sensing Letters in 2005"

Fusion of multispectral and panchromatic Satellite images using the curvelet transform

Abstract: A useful technique in various applications of remote sensing involves the fusion of different types of satellite images, namely multispectral (MS) satellite images with a high spectral and low spatial resolution and panchromatic (Pan) satellite image with a low spectral and high spatial resolution. Recent studies show that wavelet-based image fusion provides high-quality spectral content in fused images. However, the results of most wavelet-based methods of image fusion have a spatial resolution that is less than that obtained via the Brovey, intensity-hue-saturation, and principal components analysis methods of image fusion. We introduce an improved method of image fusion which is based on the amelioration de la resolution spatiale par injection de structures (ARSIS) concept using the curvelet transform, because the curvelet transform represents edges better than wavelets. Because edges are fundamental in image representation, enhancing the edges is an effective means of enhancing spatial resolution. Curvelet-based image fusion has been used to merge a Landsat Enhanced Thematic Mapper Plus Pan and MS image. The proposed method simultaneously provides richer information in the spatial and spectral domains.

Accuracy of differential shift estimation by correlation and split-bandwidth interferometry for wideband and delta-k SAR systems

Abstract: Estimation of differential shift of image elements between two synthetic aperture radar (SAR) images is the basis for many applications, like digital elevation model generation or ground motion mapping. The shift measurement can be done nonambiguously on the macro scale at an accuracy depending on the range resolution of the system or on the micro scale by employing interferometric methods. The latter suffers from phase cycle ambiguities and requires phase unwrapping. Modern wideband high-resolution SAR systems boast resolutions as small as a few tens of a wavelength. If sufficiently many samples are used for macro-scale shift estimation, the accuracy can be increased to a small fraction of a resolution cell and even in the order of a wavelength. Then, accurate absolute ranging becomes precise enough to support phase unwrapping or even make it obsolete. This letter establishes a few fundamental equations on the accuracy bounds of shift estimation accuracy for several algorithms: coherent speckle correlation, incoherent speckle correlation, split-band interferometry, a multifrequency approach, and correlation of point scatterers in clutter. It is shown that the performance of split-band interferometry is close to the Crame/spl acute/r-Rao bound for a broad variety of bandwidth ratios. Based on these findings, Delta-k systems are proposed to best take advantage of the available radar bandwidth.

On the impact of PCA dimension reduction for hyperspectral detection of difficult targets

Abstract: Due to constraints both at the sensor and on the ground, dimension reduction is a common preprocessing step performed on many hyperspectral imaging datasets. However, this transformation is not necessarily done with the ultimate data exploitation task in mind-for example, target detection or ground cover classification. Indeed, theoretically speaking it is possible that a lossy operation such as dimension reduction might have a negative impact on detection performance. This notion is investigated experimentally using real-world hyperspectral imaging data. The popular principal components transform [aka. principal components analysis (PCA)] is used to explore the impact that dimension reduction has on adaptive detection of difficult targets in both the reflective and emissive regimes. Using seven state-of-the-art algorithms, it is shown that in many cases PCA can have a minimal impact on the detection statistic value for a target that is spectrally similar to the background against which it is sought.

A novel algorithm for ship detection in SAR imagery based on the wavelet transform

Abstract: Carrying out an effective control of fishing activities is essential to guarantee a sustainable exploitation of sea resources. Nevertheless, as the regulated areas are extended, they are difficult and time consuming to monitor by means of traditional reconnaissance methods such as planes and patrol vessels. On the contrary, satellite-based synthetic aperture radar (SAR) provides a powerful surveillance capability allowing the observation of broad expanses, independently from weather effects and from the day and night cycle. Unfortunately, the automatic interpretation of SAR images is often complicated, even though undetected targets are sometimes visible by eye. Attending to these particular circumstances, a novel approach for ship detection is proposed based on the analysis of SAR images by means of the discrete wavelet transform. The exposed method takes advantage of the difference of statistical behavior among the ships and the surrounding sea, interpreting the information through the wavelet coefficients in order to provide a more reliable detection. The analysis of the detection performance over both simulated and real images confirms the robustness of the proposed algorithm.

Generation of wide-swath and high-resolution SAR images from multichannel small spaceborne SAR systems

Abstract: Future spaceborne synthetic aperture radar (SAR) systems will be required to produce high-resolution imagery over a wide area of surveillance. However, the minimum antenna area constraint makes it a contradiction to simultaneously obtain both unambiguous wide-area and high azimuth resolution. To overcome this limitation, a technique has been suggested that combines a broad illumination source with multiple receiving channels. Then, the coherent combination of the recorded multichannel signals will allow for the unambiguous SAR mapping of a wide ground area with fine azimuth resolution. This letter first gives an overview of current research work carried out about the generation of wide-swath and high-resolution SAR images from multichannel small spaceborne SAR systems, and then a space-time adaptive processing (STAP) approach combined with conventional SAR imaging algorithms is presented, which could be of help to overcome the existing difficulties in data processing. The main idea of the approach is to use a STAP-based method to properly overcome the aliasing affect caused by the lower pulse repetition frequency and thereby retrieve the unambiguous azimuth wide (full) spectrum signal from the received signal. Following this operation, conventional SAR data processing tools can be applied to fully focus the SAR images. The performance of the approach is also discussed in this letter. The approach has the advantages of simplicity, robustness, and high efficiency.

Analytical derivation of the vegetation optical depth from the microwave polarization difference index

Abstract: A numerical solution for the canopy optical depth in an existing microwave-based land surface parameter retrieval model is presented. The optical depth is derived from the microwave polarization difference index and the dielectric constant of the soil. The original procedure used an approximation in the form of a logarithmic decay function to define this relationship and was derived through a series of lengthy polynomials. These polynomials had to be recalculated when the scattering albedo or antenna incidence angle changes. The new procedure is computationally more efficient and accurate.

Band selection based on feature weighting for classification of hyperspectral data

Abstract: A new feature weighting method for band selection is presented, which is based on the pairwise separability criterion and matrix coefficients analysis. Through decorrelation of each class by principal component transformation, the criterion value of any band subset is the summations of the values of individual bands of it for the transformed feature space, and thus the computation amounts of calculating criteria of each band combinations are reduced. Following it, the corresponding matrix coefficients analysis is done to assign weights to original bands. As feature weighting considers little about the spectral correlation, the redundant bands are removed by choosing those with lower correlation coefficients than a preset threshold. Hyperspectral data classification experiments show the effectiveness of the new band selection method.

Precise topography- and aperture-dependent motion compensation for airborne SAR

Abstract: Efficient synthetic aperture radar (SAR) processing algorithms are unable to exactly implement the aperture- and topography-dependent motion compensation due to the superposition of the synthetic apertures of several targets having different motion errors and potentially different topographic heights. Thus, during motion compensation, a reference level is assumed, resulting in residual phase errors that impact the focusing, geometric fidelity, and phase accuracy of the processed SAR images. This letter proposes a new short fast Fourier transform-based postprocessing methodology capable of efficient and precise compensation of these topography- and aperture-dependent residual phase errors. In addition to wide beamwidth (very high resolution) SAR systems, airborne repeat-pass interferometry especially benefits from this approach, as motion compensation can be significantly improved, especially in areas with high topographic changes. Repeat-pass interferometric data of the E-SAR system of the German Aerospace Center (DLR) are used to demonstrate the performance of the proposed approach.

A band selection technique for spectral classification

Abstract: In hyperspectral remote sensing, sensors acquire reflectance values at many different wavelength bands, to cover a complete spectral interval. These measurements are strongly correlated, and no new information might be added when increasing the spectral resolution. Moreover, the higher number of spectral bands increases the complexity of a classification task. Therefore, feature reduction is a crucial step. An alternative would be to choose the required sensor bands settings a priori. In this letter, we introduce a statistical procedure to provide band settings for a specific classification task. The proposed procedure selects wavelength band settings which optimize the separation between the different spectral classes. The method is applicable as a band reduction technique, but it can as well serve the purpose of data interpretation or be an aid in sensor design. Results on a vegetation classification task show an improvement in classification performance over feature selection and other band selection techniques.

Study of surface brightness from backscattered laser intensity: calibration of laser data

Abstract: Systematic laboratory measurements of laser backscatter intensity are presented for brightness calibration targets, and a calibration scheme for airborne laser scanner intensity data is proposed. Thus far, the use of these data has been partly hampered by the variability of the intensity with time, and no test fields have been available for airborne reflectance calibration. Portable brightness targets (tarps), with nominal reflectances from 5% to 70%, were manufactured, and, based on these measurements, found suitable for lidar reflectance standards. Furthermore, the variability of the recorded intensity from the tarps as a function of incidence angle was low. The measurements also provide new information on the surface albedo dependence of backscattering effects: as the surface brightness increases from 5% to 70%, the hotspot brightness peak amplitudes increase by 20% to 30%, and their apparent widths reduce to a half, which implies that hotspots could be used as an albedo discriminator.

On the generation of ERS/ENVISAT DInSAR time-series via the SBAS technique

Abstract: We exploit the small baseline subset (SBAS) algorithm for generating deformation time-series from SAR data acquired by sensors with different characteristics but with the same illumination geometry. In particular, our approach is focused on the use of European Remote Sensing (ERS) and ENVISAT satellite data, the latter acquired by the Advanced Synthetic Aperture Radar sensor on the IS2 swath. The proposed solution is oriented to investigate large-scale displacements with a relatively low spatial resolution (about 100/spl times/100 m) and implements an easy but effective combination of ERS and ENVISAT multilook interferograms which benefits of the temporal overlap between the acquisitions of the two sensors. Moreover, the algorithm does not rely on specific hypothesis on the spatial or temporal characteristics of the investigated deformations. Presented results, achieved on a synthetic aperture radar dataset relevant to the Napoli city area (Italy), confirm the validity of the approach.

Total zero Doppler Steering-a new method for minimizing the Doppler centroid

Abstract: This letter presents a new method, called total Zero Doppler steering, to perform yaw and pitch steering for spaceborne synthetic aperture radar (SAR) systems. The new method reduces the Doppler centroid to theoretically 0 Hz, independent of the range position of interest. Residual errors are only due to pointing inaccuracy or due to approximations in the implementation of the total zero Doppler steering law. This letter compares the new method with currently applied methods. The attitude angles and the residual Doppler centroid frequencies are calculated and depicted exemplarily for the parameters of TerraSAR-X, for which the new method will be implemented and used. The new method provides a number of advantages. The low residual Doppler centroid and the reduced variation of the Doppler centroid over range allow a more accurate Doppler centroid estimation. Due to the low residual Doppler centroid, the synthetic aperture radar (SAR) processing can be alleviated, since the range cell migration is reduced and the Doppler frequencies are low. This facilitates the use of very efficient processing algorithms, which are based on approximations whose quality is better for low Doppler frequencies. The new method will furthermore optimize the overlap of the azimuth spectra of SAR image pairs for cross-track interferometry. Low Doppler centroids will also reduce the impact of coregistration errors on the interferometric phase. Furthermore, scalloping corrections in the ScanSAR processing are alleviated due to the low variation of the Doppler centroid over range.

Simultaneous spline approximation and topographic analysis for lidar elevation data in open-source GIS

Abstract: Application of a spline approximation method to computation and analysis of lidar-based digital elevation models is investigated to determine its accuracy and capability to create surfaces at different levels of detail. Quadtree segmentation that adapts to the spatial heterogeneity of data points makes the method feasible for large datasets. The results demonstrate the importance of smoothing for the surface accuracy and noise reduction. A tension parameter is effective for tuning the level of detail in the elevation surface. Simultaneous computation of topographic parameters is applied to extraction of sand dunes' features for assessment of dune migration and beach erosion.

A GIS numerical framework to study the process basis of scaling statistics in river networks

Abstract: A new geographic information system (GIS) numerical framework (NF), called CUENCAS, for flows in river networks is presented The networks are extracted from digital elevation models (DEMs) The program automatically partitions a basin into hillslopes and channel links that are required to correspond to these features in an actual terrain To investigate the appropriate DEM resolution for this correspondence, we take a high-resolution DEM at 10-m pixel size, and create DEMs at eight different resolutions in increments of 10 m by averaging The extracted networks from 10-30 m remain about the same, even though there is a tenfold reduction in the number of pixels By contrast, the extracted networks show increasing distortions of the original network from 40-90 m DEMs We show the presence of statistical self-similarity (scaling) in the probability distributions of drainage areas in a Horton-Strahler framework using CUENCAS The NF for flows takes advantage of the hillslope-link decomposition of an actual terrain and specifies mass and momentum balance equations and physical parameterizations at this scale These equations are numerically solved An application of NF is given to test different physical assumptions that produce statistical self-similarity in spatial peak flow statistics in a Horton-Strahler framework

Topography-dependent motion compensation for repeat-pass interferometric SAR systems

Abstract: This letter presents a new motion compensation algorithm to process airborne interferometric repeat-pass synthetic aperture radar (SAR) data. It accommodates topography variations during SAR data processing, using an external digital elevation model. The proposed approach avoids phase artifacts, azimuth coregistration errors, and impulse response degradation, which usually appear due to the assumption of a constant reference height during motion compensation. It accurately modifies phase history of all targets before azimuth compression, resulting in an enhanced image quality. Airborne L-band repeat-pass interferometric data of the German Aerospace Center experimental airborne SAR (E-SAR) is used to validate the algorithm.

Superresolution mapping using a Hopfield neural network with lidar data

Abstract: Superresolution mapping is a set of techniques to obtain a subpixel map from land cover proportion images produced by soft classification. Together with the information from the land cover proportion images, supplementary information at the subpixel level can be used to produce more detailed and accurate land cover maps. This research aims to use the elevation data from light detection and ranging (lidar) as an additional source of information for superresolution mapping using the Hopfield neural network (HNN). A new height function was added to the energy function of the HNN for superresolution mapping. The value of the height function was calculated for each subpixel of a certain class based on the Gaussian distribution. A set of simulated data was used to test the new technique. The results suggest that 0.8-m spatial resolution digital surface models can be combined with optical data at 4-m spatial resolution for superresolution mapping.

Accurate estimation of correlation in InSAR observations

Abstract: Interferometric synthetic aperture radar (InSAR) correlation, a measure of the similarity of two radar echoes, provides a quantitative measure of surface and subsurface scattering properties and hence surface composition and structure. Correlation is observed by comparing the radar return across several nearby radar image pixels, but estimates of correlation are biased by finite data sample size and any underlying interferometer fringe pattern. We present a method for correcting bias in InSAR correlation measurements resulting in significantly more accurate estimates, so that inverse models of surface properties are more useful. We demonstrate the value of the approach using data collected over Antarctica by the Radarsat spacecraft.

Open water detection from Baltic Sea ice Radarsat-1 SAR imagery

Abstract: An algorithm for open water and sea ice discrimination for Radarsat-1 ScanSAR images is presented. The algorithm is based on segmentation and local synthetic aperture radar signal intensity autocorrelation. The algorithm performance is evaluated by comparing the results to operational digitized ice charts, in which the sea ice information is based on human interpretation of multiple data sources, including remote sensing data. The algorithm locates the open water of the digitized ice charts with about 90% accuracy.

Building characterization using L-band polarimetric interferometric SAR data

Abstract: This letter proposes a building characterization technique for L-band polarimetric interferometric synthetic aperture radar (SAR) data. This characterization consists of building identification and height estimation. Initially, a polarimetric interferometric segmentation is performed to isolate buildings from their surroundings. This classification identifies three basic categories: single bounce, double bounce, and volume diffusion. In order to compensate for the misclassifications among the volume and the double-bounce classes, interferometric phases given by the high-resolution Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) method are analyzed. Once buildings are localized, a phase-to-height procedure is applied to retrieve building height information. The method is validated using E-SAR, German Aerospace Center (DLR) fully polarimetric SAR data, at L-band, repeat-pass mode, over the Oberpfaffenhofen, Germany, test site, with a spatial resolution of 1.5 m in range and azimuth. More than 80% of buildings are retrieved with acceptably accurate height estimates.

Interference suppression in synthesized SAR images

Abstract: Radio interferences are becoming more and more an important source for image degradation in synthetic aperture radar (SAR) imaging. Especially at longer wavelengths, interferences are often very strong, and their suppression is required during data processing. However, at shorter wavelengths, interferences are often not obvious in the image amplitude, and filtering is not performed in an operational way. Nevertheless, interferences might significantly degrade the image phase, and the estimation of sensitive parameters like interferometric coherence or polarimetric descriptors becomes imprecise. Interference suppression is usually performed on the raw data, which are in most cases not available to the end-user. In this letter, a new interference suppression method for focused SAR images is proposed. Its performance is tested on interferometric repeat-pass data acquired by the German Aerospace Agency's experimental SAR system (E-SAR) at L-band.

Assessment of deforestation in near real time over the Brazilian Amazon using multitemporal fraction images derived from Terra MODIS

Abstract: We present a methodology for rapidly assessing deforestation over the Amazon region needed for policy intervention. We use soil fraction images generated from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 250-m spatial resolution. Results showed reasonable agreement with higher resolution Landsat data (r/sup 2/=0.73) for our study area. MODIS data are promising for near real-time deforestation monitoring, previously not practical with Landsat data.

Frequency dispersion compensation in time reversal techniques for UWB electromagnetic waves

Abstract: The invariance of the wave equation under time reversal enables optimal refocusing of ultrawideband waves by time-reversal (TR) arrays. This forms the basis of recently developed TR techniques for selective (re-)focusing and inverse scattering applications. However, in electromagnetic sensing applications involving lossy or dispersive media, such as earth media, time invariance is lost and TR techniques can be significantly degraded. To alleviate this problem, a method to compensate dispersion in TR applications is proposed here. The method is based on short-time Fourier transforms and is shown to improve refocusing.

An electromagnetic approach based on neural networks for the GPR investigation of buried cylinders

Abstract: In this letter, neural networks (NNs) are used to reconstruct the geometric and dielectric characteristics of buried cylinders. The NN is designed to work with input data extracted from the transient electric fields scattered by the target. To this aim, a simple simulation of a typical ground-penetrating radar setting is performed and different sets of data examined. Moreover, different neural network algorithms have been exploited, and results have been compared. Finally, the "robustness" of the proposed approach has been tested against noisy data and against uncertainties in the modelization.

A semilabeled-sample-driven bagging technique for ill-posed classification problems

Abstract: In this letter, a semilabeled-sample-driven bootstrap aggregating (bagging) technique based on a co-inference (inductive and transductive) framework is proposed for addressing ill-posed classification problems. The novelties of the proposed technique lie in: 1) the definition of a general classification strategy for ill-posed problems by the joint use of training and semilabeled samples (i.e., original unlabeled samples labeled by the classification process); and 2) the design of an effective bagging method (driven by semilabeled samples) for a proper exploitation of different classifiers based on bootstrapped hybrid training sets. Although the proposed technique is general and can be applied to any classification algorithm, in this letter multilayer perceptron neural networks (MLPs) are used to develop the basic classifier of the proposed architecture. In this context, a novel cost function for the training of MLPs is defined, which properly considers the contribution of semilabeled samples in the learning of each member of the ensemble. The experimental results, which are obtained on different ill-posed classification problems, confirm the effectiveness of the proposed technique.

Using FCMC, FVS, and PCA techniques for feature extraction of multispectral images

Abstract: In this letter, a new nonlinear approach based on a combination of the fuzzy c-means clustering (FCMC), feature vector selection and principal component analysis (PCA) is proposed to extract features of multispectral images when a very large number of samples need to be processed. The main contribution of this letter is to provide a preprocessing method for classifying these images with higher accuracy compared to the single PCA and kernel PCA. Finally, some experimental results demonstrate that our proposed approach is effective and efficient in analyzing multispectral images.

Characterization and quantification of data voids in the shuttle Radar topography mission data

Abstract: The goal of this study was to characterize and quantify the occurrence of data voids in data from the Shuttle Radar Topography Mission (SRTM) for the conterminous United States. For this purpose, SRTM data and corresponding data from the national elevation data were downloaded in 21 samples spatially organized to cover the main topography of the U.S. Void locations in SRTM data were compared to terrain attributes and subsequently the area of individual data voids to the same attributes. It was found that data voids amounted to 0.3% of the total dataset. Data voids were found in all topographic settings but more often in slopes steeper than approximately 20/spl deg/ that face south (170/spl deg/), and also in flat areas such as lakes and rivers. It was also found that more than 50% of all data voids were composed of connected pixels in groups less than six pixels. The largest data voids could be attributed to water bodies, while the rest could be explained by terrain-radar interaction characteristics.

Wideband measurements of ice sheet attenuation and basal scattering

Abstract: We are developing a multifrequency multistatic synthetic aperture radar (SAR) for determining polar ice sheet basal conditions. To obtain data for designing and optimizing radar performance, we performed field measurements with a network-analyzer-based system during the 2003 field season at the North Greenland Ice Core Project camp (75.1 N and 42.3 W). From the measurements, we determine the ice sheet complex transfer function over the frequency range from 110-500 MHz by deconvolving out the system transfer function. Over this frequency range, we observe an increase in total loss of 8/spl plusmn/2.5 dB using a linear regression to the log-scale data. With the ice sheet transfer function and an ice extinction model, we estimate the return loss from the basal surface to be approximately 37 dB. These measurements have broad applicability to interpreting radar-sounding data, which are widely used in glaciological studies of the polar ice sheets. These data have also been used in the link budget for the design considerations of the multifrequency multistatic SAR system.

Adaptive inverse synthetic aperture radar imaging for nonuniformly moving targets

Abstract: A novel adaptive inverse synthetic aperture radar (ISAR) imaging technique is proposed for targets with nonuniform motion. The proposed algorithm is referred to as the generalized range-Doppler (GRD) ISAR imaging technique and is based on the fractional Fourier transform (FRFT). By utilizing this technique, clear ISAR imaging can be achieved for nonuniformly moving targets without involvement of complex motion compensation. Simulation results have proved that the new algorithm is robust and also computationally efficient as compared with previously reported algorithms such as joint time-frequency (JTF) imaging.

Correlation-based band-ordering heuristic for lossless compression of hyperspectral sounder data

Abstract: A novel algorithm for the lossless compression of hyperspectral sounding data is presented. The algorithm rests upon an efficient technique for three-dimensional image band reordering. The technique is based on a correlation factor. The correlation-based band ordering gives 5% higher compression ratios than natural ordering does. On the other hand, the obtained compression ratios are within a percent of those produced by optimal ordering, but the computational time is much lower compared to the optimal ordering. The low computational complexity of the algorithm is based on the use of correlation for the band ordering. Moreover, the algorithm results in 7% to 12% improvement over fast nearest neighbor reordering scheme versions of JPEG-LS and the context-based adaptive lossless image codec algorithms.

Polarimetric formulation of the visibility function equation including cross-polar antenna patterns

Abstract: The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission will be the first one using two-dimensional aperture synthesis radiometry for Earth observation. This study presents the formulation that relates instrument observables and brightness temperature maps including cross-polar antenna voltage patterns, which may be also different from element to element. Finally, the radiometric accuracy degradation if cross-polar patterns are neglected in the image reconstruction is studied.