Abstract
Video images captured at long range often show low-contrast floating objects of interest on a sea surface. A comparative experimental study of the statistical characteristics of reflections from floating objects and from the agitated sea surface showed differences in the correlation and spectral characteristics of these reflections. The functioning of the recently proposed modified matched subspace detector (MMSD) is based on the separation of the observed data spectrum on two subspaces: relatively low and relatively high frequencies. In the literature, the MMSD performance has been evaluated in general and using only a sea model (i.e., additive Gaussian background clutter). This paper extends the performance evaluating methodology for low contrast object detection using only a real sea dataset. The methodology assumes an object of low contrast if the mean and variance of the object and the surrounding background are the same. The paper assumes that the energy spectrum of the object and the sea are different. The paper investigates a scenario in which an artificially created model of a floating object with specified statistical parameters is placed on the surface of a real sea image. The paper compares the efficiency of the classical matched subspace detector (MSD) and MMSD for detecting low-contrast objects on the sea surface. The article analyzes the dependence of the detection probability at a fixed false alarm probability on the difference between the statistical means and variances of a floating object and the surrounding sea.
Highlights
We tackle the problem of multi-pixel floating objects detection in image sequences, which arises in search and track video systems [1,2,3,4,5,6,7,8,9,10,11]
The aim of this paper is to study the performance of two detectors (MSD and modified matched subspace detector (MMSD)) in the case of low-contrast floating objects detection
In this paper, using the experimental data, we investigate the relationship between two techniques for the detection of small low contrast floating objects on the sea surface in image sequences: these are the well-known matched subspace detector (MSD) and recently proposed MMSD techniques [18]
Summary
We tackle the problem of multi-pixel floating objects detection in image sequences, which arises in search and track video systems [1,2,3,4,5,6,7,8,9,10,11]. The common drawbacks of the published papers are the assumption that the background and channel noise are almost Gaussian processes and the lack of a low contrast target model To eliminate these shortcomings, this study uses images of real sea surfaces in various weather conditions and determines the contrast of a floating object as the difference between the statistical averages and the variances of the compared surfaces. This paper investigates the dependence of the detection probability on the difference between the mean and variance of the floating object and the surrounding sea surface. For such a study, it is necessary to change the values of these differences. The aim of this paper is to study the performance of two detectors (MSD and MMSD) in the case of low-contrast floating objects detection
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