Multispectral Filter Arrays: Recent Advances and Practical Implementation

Lapray, Pierre-Jean; Wang, Fudi; Thomas, Jean‐Baptiste; Gouton, Pierre

doi:10.3390/s141121626

Cited by 227 publications

(173 citation statements)

References 79 publications

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“…Alternatives are hyperspectral cameras which grab twodimensional frame format images based on tuneable filters (Saari et al, 2009;Lapray et al, 2014;Aasen et al, 2015). Some of these cameras acquire the image cube as a time dependent image sequence whilst others grab the entire cube at the same time, but at the cost of having low resolution images (Aasen et al, 2015).…”

Section: Hyperspectral Camerasmentioning

confidence: 99%

ORIENTATION AND CALIBRATION REQUIREMENTS FOR HYPERPECTRAL IMAGING USING UAVs: A CASE STUDY

Tommaselli

Berveglieri

Oliveira

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Flexible tools for photogrammetry and remote sensing using unmanned airborne vehicles (UAVs) have been attractive topics of research and development. The lightweight hyperspectral camera based on a Fabry-Pérot interferometer (FPI) is one of the highly interesting tools for UAV based remote sensing for environmental and agricultural applications. The camera used in this study acquires images from different wavelengths by changing the FPI gap and using two CMOS sensors. Due to the acquisition principle of this camera, the interior orientation parameters (IOP) of the spectral bands can vary for each band and sensor and changing the configuration also would change these sets of parameters posing an operational problem when several bands configurations are being used. The objective of this study is to assess the impact of use IOPs estimated for some bands in one configuration for other bands of different configuration the FPI camera, considering different IOP and EOP constraints. The experiments were performed with two FPI-hyperspectral camera data sets: the first were collected 3D terrestrial close-range calibration field and the second onboard of an UAV in a parking area in the interior of São Paulo State.

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Section: Hyperspectral Camerasmentioning

confidence: 99%

ORIENTATION AND CALIBRATION REQUIREMENTS FOR HYPERPECTRAL IMAGING USING UAVs: A CASE STUDY

Tommaselli

Berveglieri

Oliveira

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The availability of new lightweight sensors (Aasen et al, 2015;Gupta et al, 2008;Hagen and Kudenov, 2013;Lapray et al, 2014) and the improvement of the autonomy of unmanned aerial vehicles (UAVs) have contributed for applications in forestry, agriculture, water and natural resources management (e.g., Goetz, 2009;Honkavaara et al, 2013). Research and monitoring activities have been benefited by the possibility of acquiring images with high spatial, temporal and spectral resolution, which enables more detailed studies based on image analysis.…”

Section: Introductionmentioning

confidence: 99%

Estimating Exterior Orientation Parameters of Hyperspectral Bands Based on Polynomial Models

Berveglieri¹,

Tommaselli²,

Honkavaara³

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Hyperspectral camera operating in sequential acquisition mode produces spectral bands that are not recorded at the same instant, thus having different exterior orientation parameters (EOPs) for each band. The study presents experiments on bundle adjustment with time-dependent polynomial models for band orientation of hyperspectral cubes sequentially collected. The technique was applied to a Rikola camera model. The purpose was to investigate the behaviour of the estimated polynomial parameters and the feasibility of using a minimum of bands to estimate EOPs. Simulated and real data were produced for the analysis of parameters and accuracy in ground points. The tests considered conventional bundle adjustment and the polynomial models. The results showed that both techniques were comparable, indicating that the time-dependent polynomial model can be used to estimate the EOPs of all spectral bands, without requiring a bundle adjustment of each band. The accuracy of the block adjustment was analysed based on the discrepancy obtained from checkpoints. The root mean square error (RMSE) indicated an accuracy of 1 GSD in planimetry and 1.5 GSD in altimetry, when using a minimum of four bands per cube.

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“…In most cases, range and spectral information was assumed to be available for each wavelength. Recently, the implementation of mosaic filters, or multispectral filter arrays, to produce simultaneous multispectral images on a single frame read-out has been pursued by several groups [12], [13]. In such cases, a single wavelength (out of the L wavelengths) is acquired at each spatial location and an interpolation scheme is thus required to recover the L full intensity profiles.…”

Section: Introductionmentioning

confidence: 99%

Bayesian restoration of reflectivity and range profiles from subsampled single-photon multispectral Lidar data

Altmann

Tobin

Maccarone

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-In this paper, we investigate the recovery of range and spectral profiles associated with remote three-dimensional scenes sensed via single-photon multispectral Lidar (MSL). We consider different spatial/spectral sampling strategies and compare their performance for similar overall numbers of detected photons. For a regular spatial grid, the first strategy consists of sampling all the spatial locations of the grid for each of the wavelengths. Conversely, the three other strategies consist, for each spatial location, of acquiring a reduced number of wavelengths, chosen randomly or in a deterministic manner. We propose a fully automated computational method, adapted for the different sampling strategies in order to recover the target range profile, as well as the reflectivity profiles associated with the different wavelengths. The performance of the four sampling strategies is illustrated using a single photon MSL system with four wavelengths. The results presented demonstrate that although the first strategy usually provides more accurate results, the subsampling strategies do not exhibit a significant performance degradation, particularly for extremely photonstarved data (down to one photon per pixel on average).

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Multispectral Filter Arrays: Recent Advances and Practical Implementation

Cited by 227 publications

References 79 publications

ORIENTATION AND CALIBRATION REQUIREMENTS FOR HYPERPECTRAL IMAGING USING UAVs: A CASE STUDY

ORIENTATION AND CALIBRATION REQUIREMENTS FOR HYPERPECTRAL IMAGING USING UAVs: A CASE STUDY

Estimating Exterior Orientation Parameters of Hyperspectral Bands Based on Polynomial Models

Bayesian restoration of reflectivity and range profiles from subsampled single-photon multispectral Lidar data

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