Techniques for detection of multiple, extended, and low contrast targets in infrared maritime scenarios

Ondini, Aurora; Marsiglia, Gianluca; Fortunato, Luca; Balzarotti, Giorgio

doi:10.1117/1.2403844

Cited by 20 publications

(8 citation statements)

References 13 publications

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“…Based on this shape Target-related information. There are intensity, shape, motion, 3D distance, and frequency target information. information, there are matched filters (template matching) [1,4,5], multi-scale methods [6][7][8], and radial symmetry-based method [9]. Shape information is highly effective in removing cloud clutter and may reduce ground clutter, sun-glint, and stripe-like scan noise.…”

Section: Target 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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Section: Target 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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“…Template matching technique has been extensively studied and used in pattern recognition application, and some template matching methods for infrared small detection based on normalized crosscorrelation was presented [21,22]. In addition, principal component analysis (PCA) can reduce redundancies in high dimensional by using low dimensional linear subspace, the projection coefficients templates obtained from principal component analysis (PCA) and the nonlinear correlation similarity measurement were proposed for template matching [23,24].…”

Section: Related Workmentioning

confidence: 99%

Adaptive detection method of infrared small target based on target-background separation via robust principal component analysis

Wang

Qin

2015

Infrared Physics & Technology

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“…The main purpose of these methods is to design a filter in a way, to satisfy the stated purpose. Authors in [1] present a template matching based algorithm for infrared targets. The main concentrate in this work is on specific area of sea around the horizon, where common target detection methods have many false-positive and false-negative results.…”

Section: Introductionmentioning

confidence: 99%

A new method for detecting variable-size infrared targets

2014

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In this paper, a new method to detect small targets in infrared images is presented. The proposed method is based on the optical responses of infrared photodetectors, mainly point spread function (PSF). The effects of PSF on gray level and shape of the targets is used to distinguish the targets from background clutter. Also, a novel operator called Lapalacian of Point Spread Function (LoPSF) is proposed to identify location and size of the infrared targets. Since detecting the variable-size targets in infrared search and track systems (IRST) is of critical importance, unlike previous methods of target detection, the proposed method can robustly detect variable-size targets. The proposed algorithm is applied on a set of real infrared images which are captured under different conditions such as target size, target distance, background clutter etc.. Simulation results demonstrate the effectiveness and validity of the proposed method in comparison with the other conventional methods.

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Techniques for detection of multiple, extended, and low contrast targets in infrared maritime scenarios

Cited by 20 publications

References 13 publications

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

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

Adaptive detection method of infrared small target based on target-background separation via robust principal component analysis

A new method for detecting variable-size infrared targets

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