Characterization of dynamic sea scenarios with infrared imagers

López-Alonso, José Manuel; Alda, Javier

doi:10.1016/j.infrared.2004.06.003

Cited by 12 publications

(11 citation statements)

References 12 publications

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“…Other forms of still imagery have been used to study glitter, including stereo photos [78][79][80][81][82][83][84][85][86] (as discussed by Jähne, Klinke, and Waas [87] and Monaldo and Kasevich [25]), polarimetric imagery [88], infrared imagery [89][90][91], satellite imagery [92][93][94][95], and other imagery types [96].…”

Section: Photographic Data Collectionsmentioning

confidence: 99%

Characterization of Sun Glitter Statistics in Ocean Video

Rainey¹,

Hallenborg²

2013

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OBJECTIVESunlight reflected on the moving sea surface, often referred to as glitter, is usually considered a hindrance to analysis of ocean scenes, and glitter removal algorithms are often employed in pre-processing of ocean imagery. However, glitter statistics can provide valuable insight into sea surface behavior, both from the standpoint of characterizing image "clutter" and gaining a better understanding of sea surface roughness. In this work, sun glitter is observed through shore-based video of the ocean collected at various optical wavelengths (visible and infrared), and various statistical properties of the collected video are analyzed. RESULTS A MATLAB® tool has been developed with which to analyze several key statistics of the collected video. This report details the functionality of this tool and demonstrates the behavior of a number of spatial-, temporal-, and spectral-domain statistics of glitter video. A detailed background on previous glitter-related research is also given.

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Section: Photographic Data Collectionsmentioning

confidence: 99%

Characterization of Sun Glitter Statistics in Ocean Video

Rainey¹,

Hallenborg²

2013

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“…So, the static clutter can be removed by frame difference [32]. Principal component analysis (PCA) for multi-frames can remove temporal noise such as sun-glint [33].…”

Section: Background Information-based Target Detectionmentioning

confidence: 99%

Double Layered-Background Removal Filter for Detecting Small Infrared Targets in Heterogenous Backgrounds

Kim

2010

J Infrared Milli Terahz Waves

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Detecting small targets is essential for mitigating the sea-based Infrared search and track (IRST) problem. It is easy to detect small targets in homogeneous backgrounds such as the sky. When targets are on the border line of heterogeneous backgrounds such as the horizon in the sky and sea surface, solving the problem of detection becomes difficult. This paper presents a novel spatial filtering method, called Double Layered-Background Removal Filter (DL-BRF), for achieving high detection rates and low false alarm rates. DL-BRF consists of a Modified-Mean Subtraction Filter (M-MSF) and a consecutive LocalDirectional Background Removal Filter (L-DBRF). M-MSF enhances the target signal and reduces background noise. L-DBRF removes horizontal structures, which upgrade the signal-to-clutter ratio and background suppression factor. L-DBRF used after M-MSF enhances the synergistic performance of horizontal target detection. Additionally, the adaptive Hysteresis threshold-based scheme is a suitable detection method. We validate the superior performance of the proposed method via three types of evaluation tests, including a real test scenario.

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“…It is possible to filter out this 'fitting noise' by applying the PCA method over the 2D beams corresponding to each group of the fitting parameters. [3][4][5][6][7][8] A 2D version of the beam shape is calculated from only two directional profiles. A more useful approach would use a 2D beamprofile image.…”

Section: Figure 3 Applying Pca To the Intensity Of A Beam At Its Besmentioning

confidence: 99%

Characterizing the shape of infrared beams

López-Alonso¹

2006

SPIE Newsroom

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is a research scholar at the infrared lab of CREOL, in the University of Central Florida. He works on the characterization of infrared detectors and systems and in EUCLID and NATO programs related to these topics. He has been on the committee of the SPIE Defense and Security (Europe) conference for the last two years, and has published and presented more than 20 papers in SPIE conferences and journals.

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Characterization of dynamic sea scenarios with infrared imagers

Cited by 12 publications

References 12 publications

Characterization of Sun Glitter Statistics in Ocean Video

Characterization of Sun Glitter Statistics in Ocean Video

Double Layered-Background Removal Filter for Detecting Small Infrared Targets in Heterogenous Backgrounds

Characterizing the shape of infrared beams

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