基于特征点分布特性的激光干扰效果评估算法

Abstract

Laser active imaging systems are usually used in region surveillance and target identification. However, the photoelectric imaging detector in the imaging systems is easy to be disturbed and this leads to errors of the recognition and even the missing of the target. Assessment of laser-dazzling effects in view of the invalidation of the target feature must be better understood. A new feature-point similarity (FPSIM) assessment algorithm is proposed. The feature accelerated segmentation testing (FAST) algorithm is used to extract feature points of the original image and disturbed image. The target area is obtained via feature-point matching, and the feature-point maintenance as well as stabilization is computed in the target area. The location of the feature points in the original image is obtained, and the local luminance and contrast distortion are compared in the same place of the two images. The normalized FPSIM is obtained via product of the feature-point maintenance, stabilization, luminance distortion and contrast distortion. The luminance imaging experiment is performed for the target by utilizing the laser active imaging system. In the experiment, the disturbed images of different disturbing powers, different intense backgrounds and different spot positions are obtained. The proposed FPSIM algorithm is used to evaluate the newly obtained laser-dazzling images, and the results show that the FPSIM reflects the varieties of the feature points in target recognition objectively. Compared with normalized mean square error (NMSE) and structural simila rity (SSIM), the FPSIM gives a more reasonable evaluation result for different laser-dazzling images. The evaluation results are more suitable for the subjective visual feeling, and FPSIM can also give the guidance of the laser active imaging system defense and application.