Výsledky vyhledávání

A Long Wave Infrared (LWIR) spectral imager (7.7 to 12.3 μ) based on cooled detector array and high resolution Circular Variable Filter (CVF)

Autor: Jacob Dolev, Uri Milman, Amir Gil, Moshe Lavi, Dario Cabib, Eran Ohel

Publikováno v: SPIE Proceedings.

Spectral imagers in the Long Wave IR spectral range (8 to 12 microns) suffer from the problem of high production costs because the existing commercial cooled array detectors are expensive, and in fact they are prohibitively expensive for many applica

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5658e633d78cd5d1e611d85868da27f8
https://doi.org/10.1117/12.2029524

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Anomaly Gas Remote Sensing and Tracking Using a Field-Portable Imaging Thermal Radiometric Spectrometer

Autor: Stanley R. Rotman, Dan G. Blumberg, Lior Sagiv, Eran Ohel

Publikováno v: 2006 IEEE 24th Convention of Electrical & Electronics Engineers in Israel.

Using a set of radiometric thermal hyperspectral data cubes, we developed an algorithm which detects the formation of an anomalous gas cloud. Once we've established the presence of the cloud in the latter images, we determine the origin of the cloud

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd625768eb99cf463ddbca11c7720e7c
https://doi.org/10.1109/eeei.2006.321072

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A three-stage approach to large-target acquisition in spectral images

Autor: Stanley R. Rotman, Dan G. Blumberg, Eran Ohel

Publikováno v: Electro-Optical and Infrared Systems: Technology and Applications II.

Over the last few years, we have developed an algorithm which detects anomalous targets in hyperspectral or multispectral images. The algorithm takes a data (image) cube with a completely unknown background, segments the cube, assigns the largest clu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::83c678f2de4c7ce57ede5f899db62bc9
https://doi.org/10.1117/12.629434

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Combining CFAR with anomaly detection at hyperspectral images

Autor: Eran Ohel, Dan G. Blumberg, Stanley R. Rotman

Publikováno v: SPIE Proceedings.

Over the last few years, we have developed an algorithm which detects anomalous targets in hyperspectral images. The algorithm takes a hyperspectral cube with a completely unknown background, segments the cube, assigns the largest clusters as backgro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c67688c360420aabc81844f491c3d92e
https://doi.org/10.1117/12.652373

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Multipixel anomaly detection in noisy multispectral images

Autor: Eran Ohel, Stanley R. Rotman, Dan G. Blumberg

Publikováno v: SPIE Proceedings.

Basing ourselves on a novel segmentation algorithm for multispectral images, we consider how to detect multipixel anomalous objects in image cubes where spectral information is available. In particular, we have developed several morphological filters

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53de029d434048c9f9bdaf57f41a1370
https://doi.org/10.1117/12.557627

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Detection of large targets in noisy hyper-spectral images

Autor: Eran Ohel, Dan G. Blumberg, Stanley R. Rotman

Publikováno v: Scopus-Elsevier

Basing ourselves on a novel segmentation algorithm for hyper-spectral images (HSI), we have considered how to detect large targets (multi-pixel anomalous objects) in image cubes with a spectral component. In particular, we have developed several filt

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a6b5fe86d7b4f49f061b2d89258c48b
http://www.scopus.com/inward/record.url?eid=2-s2.0-17444388930&partnerID=MN8TOARS