Reflective and polarimetric characteristics of urban materials

Jones, Douglas; Goldstein, Dennis H.; Spaulding, Jonathan C.

doi:10.1117/12.665012

Cited by 22 publications

(7 citation statements)

References 9 publications

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“…Cluster analysis in N-dimensional space is widely used on multivariate or multidimensional remotesensing data [12,13], particularly hyperspectral data. Clustering of monostatic laser-polarimeter data has been demonstrated experimentally [14], and Jones, et al recently applied such data clustering strategies based on nonlinear support vector machines [15]. In the previous work analytically most similar to this paper, Tyo considered the distribution of simulated polarization data in multidimensional space and derived optimum linear-combination channels using PCA [10].…”

Section: Introductionmentioning

confidence: 81%

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Polarization components analysis for invariant discrimination

Hoover

Tyo

2007

Appl. Opt.

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Linear and nonlinear components analysis of data from a monostatic laser polarimeter is developed and applied to the task of remote, nonimaging discrimination among different textures on paint and polymer coupons independent of their spatial orientations. Both principal-components analysis and nonlinear components analysis are applied to multidimensional laser data in measured Mueller matrices, with discrimination via cluster segmentation in derived linear and nonlinear constant channels. Textures on the discriminated coupons are generated by heating and illustrated in optical micrographs.

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Section: Introductionmentioning

confidence: 81%

“…(12)- (14). Equation (15) implies that the 16 elements of the rotated data are empirically uncorrelated over the set of possible observations. Equation…”

Section: Appendix Amentioning

confidence: 99%

Polarization components analysis for invariant discrimination

Hoover

Tyo

2007

Appl. Opt.

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“…This is consistent with other reported results for similar sample types under similar measurement conditions. [8][9][10][11] Therefore, we will focus on the m 11 , m 22 , and m 33 diagonal components for the remaining analysis in this paper. …”

Section: Experiments Limitationsmentioning

confidence: 99%

Influence of sensing geometry on polarimetric reflectance data

2008

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Our objective is to disseminate the importance of sensing geometry when comparing reflectance data from different polarimeters. Results are presented from an eye-safe laser scatterometer that was used to measure the Mueller matrix of samples under a diversity of sensing geometries, thus providing a common reference for instrument comparison. Data from three other polarimeters are compared to this reference, and apparent discrepancies are explained in terms of each instrument's unique experimental sensing geometry. Results are also provided showing that the degree of sensing geometry dependence varied widely among sample types.

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“…In many cases, additional measurements are made beyond 16 in order to condition the system against the effects of noise. 4,12 Use of feature extraction algorithms allows certain diagnostic tasks to be performed with subsets of the Mueller matrix elements, 13,14 which can simply data acquisition and system design. However, with the exception of simple systems such as polarimetric LIDARs that only transmit and receive on two polarization channels, 2 virtually all reported polarimeters obtain subsets of the Mueller matrix elements by measuring the full Mueller matrix and discarding the unneeded portions of the matrix.…”

Section: Introductionmentioning

confidence: 99%

Designing partial Mueller matrix polarimeters

Tyo

Johnson

Wang

et al. 2009

Polarization Science and Remote Sensing IV

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When using a MMP for a detection or identification task, a user considers certain elements of the Mueller matrix. The usual way of performing this task is to measure the full Mueller matrix and discard the unused elements. For polarimeter designs with speed, miniaturization, or other constraints it may be desirable to have a system with reduced dimensionality that measures only the important elements of the Mueller matrix as efficiently as possible. In this paper, we develop a framework that allows partial MMPs to be analyzed. Quantitative metrics are developed by considering geometrical relationships between the space spanned by a particular MMP and the space occupied by the scene components. The method is generalized to allow the effects of noise to come into the equation when noise performance is important as well.

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Reflective and polarimetric characteristics of urban materials

Cited by 22 publications

References 9 publications

Polarization components analysis for invariant discrimination

Polarization components analysis for invariant discrimination

Influence of sensing geometry on polarimetric reflectance data

Designing partial Mueller matrix polarimeters

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