Shearlet Features for Registration of Remotely Sensed Multitemporal Images

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Experimental results on multitemporal Landsat images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms

Super Resolution of Remote Sensing Images Using Edge-Directed Radial Basis Functions

Edge-Directed Radial Basis Functions (EDRBF) are used to compute super resolution(SR) image from a given set of low resolution (LR) images differing in subpixel shifts. The algorithm is tested on remote sensing images and compared for accuracy with other well-known algorithms such as Iterative Back Projection (IBP), Maximum Likelihood (ML) algorithm, interpolation of scattered points using Nearest Neighbor (NN) and Inversed Distance Weighted (IDW) interpolation, and Radial Basis Functin(RBF) . The accuracy of SR depends on various factors besides the algorithm (i) number of subpixel shifted LR images (ii) accuracy with which the LR shifts are estimated by registration algorithms (iii) and the targeted spatial resolution of SR. In our studies, the accuracy of EDRBF is compared with other algorithms keeping these factors constant. The algorithm has two steps: i) registration of low resolution images and (ii) estimating the pixels in High Resolution (HR) grid using EDRBF. Experiments are conducted by simulating LR images from a input HR image with different sub-pixel shifts. The reconstructed SR image is compared with input HR image to measure the accuracy of the algorithm using sum of squared errors (SSE). The algorithm has outperformed all of the algorithms mentioned above. The algorithm is robust and is not overly sensitive to the registration inaccuracies

Agile Multi-Scale Decompositions for Automatic Image Registration

In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Experimental results on multitemporal Landsat images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms

Front face fluorescence spectroscopy and visible spectroscopy coupled with chemometrics have the potential to characterise ripening of Cabernet Franc grapes

The potential of front-face spectroscopy for grape ripening dates discrimination was investigated on Cabernet Franc grapes from three parcels located on the Loire Valley and for six ripening dates. The 18 batches were analysed by front-face fluorescence spectroscopy and visible spectroscopy. The excitation spectra (250–310 nm, emission wavelength = 350 nm) were characterised by a shoulder at 280 nm. Grapes spectra were classified by factorial discriminant analysis (FDA). Ripening dates were well predicted by fluorescence spectra: grapes before veraison were separated from grapes after veraison and almost every ripening date was identified. The common spectroscopic space obtained by CCSWA showed that wavelengths corresponding to anthocyanin absorption in the visible were correlated to fluorescence wavelengths around the starting and ending points of the shoulder (263 and at 292 nm). Then, regression models were investigated to predict total soluble solids (TSS), total acidity, malvidin-3G, total anthocyanins and total phenolics content from visible and fluorescence spectra. To predict technological indicators (TSS and total acidity), the PLS model with visible spectra (RMSECV = 0.82°Brix or 0.96 g L−1 H2SO4) was better than those with fluorescence one (RMSECV = 1.39°Brix or 2.06 g L−1 H2SO4). For malvidin-3G and total anthocyanins, all R c 2 and R cv 2 were superior to 0.90 and RMSECV were low. Visible and fluorescence spectroscopies succeeded in predicting anthocyanin content. Concerning total phenolic, the best prediction was provided by fluorescence spectroscopy

New Observing Strategy (NOS) for Future Earth Science Missions

One of the new thrusts of the Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program is the New Observing Strategy (NOS) thrust. Its goal is to provide a framework for identifying technology advances needed to exploit newly available observational capabilities, particularly to enable the development of the information technologies needed to support planning, evaluating, implementing, and operating dynamic, multi-element sets of observing assets. In this paper, we will introduce relevant NOS terminology and some key concepts before describing the objectives, driving factors and technology goals of this new thrust

FISHing for ciliates: Catalyzed reporter deposition fluorescence in situ hybridization for the detection of planktonic freshwater ciliates

Planktonic ciliate species form multiple trophic guilds and are central components of freshwater food webs. Progress in molecular analytical tools has opened new insight into ciliate assemblages. However, high and variable 18S rDNA copy numbers, typical for ciliates, make reliable quantification by amplicon sequencing extremely difficult. For an exact determination of abundances, the classical morphology-based quantitative protargol staining is still the method of choice. Morphotype analyses, however, are time consuming and need specific taxonomic expertise. Catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) may represent a promising tool for the analysis of planktonic ciliates by combining molecular identification with microscopic quantification. We tested the applicability of CARD-FISH using nine cultured ciliate species. Eight species- and three genus-specific oligonucleotide probes were designed based on their 18S rRNA genes. The CARD-FISH protocol was adapted and the specificity of probes was established. We subsequently examined the precision of quantitation by CARD-FISH on single cultures and mock assemblages. Successful tests on lake water samples proved that planktonic ciliates could be identified and quantified in field samples by CARD-FISH. Double hybridizations allowed studying interspecific predator prey interactions between two ciliate species. In summary, we demonstrate that CARD-FISH with species-specific probes can facilitate studies on the population dynamics of closely related, small sized or cryptic species at high sampling frequencies