Statistical detection of resolved targets in background clutter using optical/infrared imagery

Abstract

The use of optics to detect targets has been around for a long time. Early attempts at automatic target detection assumed target plus noise, which means that the targets were small compared to the pixel field of view and therefore unresolved. However, the advent of advanced focal plane technology has resulted in optical systems that can provide highly resolved target images. The intent of this paper is to develop a general solution for the detection of resolved targets in background clutter. We recognize that resolved targets obscure any background clutter that would have been visible if the targets were absent. An optimum detection algorithm is derived that compares a test statistic to a threshold and decides a target is present if the statistic is less than the threshold. We find that the detection performance depends upon (1) the apparent contrast rather than the signal to noise ratio and (2) is highly dependent on the background clutter to common system noise ratio. In fact, the target can still be detected even when the target contrast goes to zero provided the background clutter is greater than the common system noise. Computer simulations are shown to validate the theoretical detection and false alarm probabilities. The findings in this paper should be useful to engineers and scientists designing electro-optical and infrared sensors for finding resolved targets immersed in background-cluttered images.

Resolved target detection in clutter using correlated, dual-band imagery

“…20 The paper investigates resolved target detection hypothesis testing using highly correlated two-color imagery to obtain large signal processing gains to reduce clutter and extract the target's location if it is present. It extends the classical approach development of Stotts and Hoff 21 to dual-band target detection. This approach assumes that the target profile is contained in a fixed number of pixels since many applications use detection as the first step to classification and identification of the target, [22][23][24][25][26][27][28][29][30][31] namely, MF detection (leakage of background clutter into edge pixels reduces the maximum filter gain but usually not by a large amount because of the potentially large number of pixels a resolved image contains [1][2][3] ).…”

“…18 As pointed out by Goudail in a private communication, other researchers have been developing techniques for the replacement target model for some time under the topic of pattern recognition with nonoverlapping targets and background clutter. 21 The overarching approach taken by all of these researchers was to make it an estimation and detection problem rather than trying to tackle the classical approach. 20 The paper investigates resolved target detection hypothesis testing using highly correlated two-color imagery to obtain large signal processing gains to reduce clutter and extract the target's location if it is present.…”

“…32 Finally, this approach reconfirms that the electrical SNR is related to the Weber contrast 33 and the normalized noise variance, as shown by Stott and Hoff. 21 2 Background and Motivation for Two-Band Only Optical Detection Strategy In the majority of the optical target detection strategies in multiband imagery, the solution involves the likelihood ratio, and the required resolved/unresolved target and noise intensity distributions obey multivariate Gaussian probability density functions (PDFs) of the form E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 6 3 ; 6 7 2 H 0 : x ∼ Nðj n ; R n Þ…”

Front Matter: Volume 9596

“…We implement the method proposed in 2014 by Stotts and Hoff (SH14) [1] to automatically detect resolved targets embedded in background clutter. The SH14 method provides a test statistic which emphasizes comparing apparent contrast rather than signal to noise ratio.…”

“…• Estimator output estimate is a weighted Gaussian sum across all l-path estimates (a wavelet) We implement and test the target detection method proposed in 2014 by Stotts and Hoff [1] The focus of our effort was to explore the utility of the method for scenes containing maritime targets and backgrounds…”