Abstract
It has always been a serious challenge to efficiently detect infrared targets from remote sea-sky background without any prior knowledge. This is especially true when target features of different areas are irrelevant in the same image. The main contribution of this paper is to design an algorithm of judge sea-sky condition and detect infrared target, in which a two-direction local maximum (TLM) method and peak local singularity (PLS) is proposed, constant excitatory difference of Gaussians (CEDoG) operator is applied by analyzing the characteristics of the target. First and foremost, the TLM method is adopted to refine seasky area to extract the suspected sea-sky line, and design the strategy of “de-false”to realize the accurate determination of the sea-sky line. Secondly, small targets in the sea-sky area (pixels 2 × 2 to 9 × 9) are detected by applying the PLS method. Finally, CEDoG filtering method is used to suppress the background and improve the significance of the target, and high threshold OTSU method (H-OTSU) is applied to find the most significant area and self-designed area growth rule to ensure the accuracy and integrity of the maritime area target detection. Comparing with the other state-of-the-art methods in the experiments, our strategy has a robust and effective performance in terms of recall, precision, elapsed time, complexity, detection and false alarm rate.
Highlights
With the development of economy and science and technology, maritime activities continue to increased due to the complex and volatile marine environment
For more comprehensive considerations, when the connected domains with the same difference value are all larger than threshold, we select the suspicious target located at the top in the image as the final sea-sky line, the least square method is used to fit the points in the refined sea-sky line after determining sea-sky environment
In Section A, validation data sets is introduced and compared with six kinds of target detection algorithms, which are mutual wavelet energy combination algorithm to improve the target significance under the sea-sky background (WT) [5], multiscale fuzzy metric model for single background suppression (MFMM) [15], robust infrared maritime target detection based on visual attention and spatiotemporal filtering in the complex scene including the sea-sky environment (VAPFM) [10], multiscale patch-based contrast measure for small infrared target detection (MPCM) [20], infrared small target detection via non-convex rank approximation minimization joint l2,1 norm (NRAM) [23] and spatial–temporal local difference measure (STLDM) [42]
Summary
With the development of economy and science and technology, maritime activities continue to increased due to the complex and volatile marine environment. The sea-sky environment with uncertain background clutter and wave noise is still the most prone to occur, which brings great difficulties and challenges to long range maritime targets detection. This paper proposed a new strategy of infrared sea-sky environment search system by collecting the required experimental data and analysis to achieve accurate detection of any targets. (4) For maritime area, CEDoG filtering method is used to suppress the background and improve the saliency of the target, and the H-OTSU method is selected to find the most significant area and the set area growth rule to ensure accuracy and integrity of target detection These four contributions make the proposed algorithm can accurately detect infrared targets with different characteristics in different sea -sky environments.
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