Detection of leaf structures in close-range hyperspectral images using morphological fusion

Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods

Recognition and reconstruction of coherent energy with application to deep seismic reflection data

Reflections in deep seismic reflection data tend to be visible on only a limited number of traces in a common midpoint gather. To prevent stack degeneration, any noncoherent reflection energy has to be removed. In this paper, a standard classification technique in remote sensing is presented to enhance data quality. It consists of a recognition technique to detect and extract coherent energy in both common shot gathers and fi- nal stacks. This technique uses the statistics of a picked seismic phase to obtain the likelihood distribution of its presence. Multiplication of this likelihood distribution with the original data results in a “cleaned up” section. Application of the technique to data from a deep seismic reflection experiment enhanced the visibility of all reflectors considerably. Because the recognition technique cannot produce an estimate of “missing” data, it is extended with a reconstruction method. Two methods are proposed: application of semblance weighted local slant stacks after recognition, and direct recognition in the linear tau-p domain. In both cases, the power of the stacking process to increase the signal-to-noise ratio is combined with the direct selection of only specific seismic phases. The joint application of recognition and reconstruction resulted in data images which showed reflectors more clearly than application of a single technique

Processing of multispectral thermal IR data for geologic applications

Multispectral thermal IR data were acquired with a 24-channel scanner flown in an aircraft over the E. Tintic Utah mining district. These digital image data required extensive computer processing in order to put the information into a format useful for a geologic photointerpreter. Simple enhancement procedures were not sufficient to reveal the total information content because the data were highly correlated in all channels. The data were shown to be dominated by temperature variations across the scene, while the much more subtle spectral variations between the different rock types were of interest. The image processing techniques employed to analyze these data are described

Resonant coupling between localized plasmons and anisotropic molecular coatings in ellipsoidal metal nanoparticles

We present an analytic theory for the optical properties of ellipsoidal plasmonic particles covered by anisotropic molecular layers. The theory is applied to the case of a prolate spheroid covered by chromophores oriented parallel and perpendicular to the metal surface. For the case that the molecular layer resonance frequency is close to being degenerate with one of the particle plasmon resonances strong hybridization between the two resonances occur. Approximate analytic expressions for the hybridized resonance frequencies, their extinction cross section peak heights and widths are derived. The strength of the molecular - plasmon interaction is found to be strongly dependent on molecular orientation and suggest that this sensitivity could be the basis for novel nanoparticle based bio/chemo-sensing applications.Comment: 11 pages, 5 figure

Plasmonics: Localization and guiding of electromagnetic energy in metal/dielectric structures

We review the basic physics of surface-plasmon excitations occurring at metal/dielectric interfaces with special emphasis on the possibility of using such excitations for the localization of electromagnetic energy in one, two, and three dimensions, in a context of applications in sensing and waveguiding for functional photonic devices. Localized plasmon resonances occurring in metallic nanoparticles are discussed both for single particles and particle ensembles, focusing on the generation of confined light fields enabling enhancement of Raman-scattering and nonlinear processes. We then survey the basic properties of interface plasmons propagating along flat boundaries of thin metallic films, with applications for waveguiding along patterned films, stripes, and nanowires. Interactions between plasmonic structures and optically active media are also discussed