Detection of the subpixel floating objects on an agitated sea surface using an image sequence

The optical subpixel detection of the floating objects on an agitated sea surface remains a hard problem. In this paper, we conduct a comparative study and investigate the relationship between two techniques in image sequence detection: well-known matched subspace detection (MSD) and recently proposed modified MSD (MMSD). MMSD approach extends the optimum Neyman-Pearson methodology to detection of a subspace signal in correlated additive Gaussian background when the background power may be different under the null (H₀) and alternative (H₁) hypotheses. It is assumed that the background covariance structure and power under the null hypothesis are known but under the alternative hypothesis the background power can be unknown. This situation occurs in optical systems when the presence of a small point (subpixel) object decreases the background power. The proposed detector structure contains the additional adaptive corrective term in the threshold. This corrective term decreases the value of presumed threshold automatically and, therefore, increases the probability of detection. Computer simulation and experimental results have shown that the proposed detector outperforms the conventional MSD. The influence of the adaptive threshold on the detector performance has been evaluated for the example scenario of the subpixel floating object on the agitated sea surface by using the experimental and simulation results.