中文摘要：

传统基于ROD的斑点检测算法在对不同帧或当前帧的不同区域进行检测时，所采取的阈值是固定不变的，缺乏自适应性，同时也在很大程度上影响了检测效果．为了解决上述问题，提出了一种基于统计学的自适应阈值检测方法．传统检测方法仅计算各孤立点之间的灰度级差异，而该算法则是计算各点邻域块内的灰度级差异，同时利用阈值迭代及帧间的统计特性的方法来确定每一帧图像的最优阈值，提高了算法的自适应性．仿真实验结果表明，该算法的斑点检测效果比传统方法更加准确，自适应性也更高．

英文摘要：

Due to fixed threshold in detecting blotches in different frames or different regions in one frame, the tradi- tional ROD-based algorithm is lack of adaptivity, thus the detection result is affected greatly. In order to solve the above problem, an adaptive threshold detection method based on statistics was proposed in this paper. Different from traditional methods, which only compute gray level differences between isolated points, the proposed method can compute gray level differences within the neighborhood blocks of the points. Besides, the optimal threshold is determined by iterative threshold and the statistical properties between frames, so the adaptivity of the algorithm is improved. The simulation results show that the proposed method has more accurate blotch detection effect and better adaptivity than traditional ones.