摘要： 传统运动图像斑点检测算法通过降低阈值来提高正确检测率，但较高的错误检测率直接影响其后的斑点修复结果。为最大化正确检测率与错误检测率之间的比值，在SROD检测算法的基础上提出改进的斑点检测算法。引入自适应多阈值的概念，对同一帧图像中的不同斑点进行自动收敛，找到合适的阈值，采用纹理匹配方法减小斑点区域中由于运动矢量估计导致的偏差。对实际破损以及人工添加斑点的图像序列进行性能评估，结果表明，改进算法能在得到较高正确检测率的同时降低错误检测率。

关键词: 斑点检测, 自适应多阈值, 纹理匹配, 迭代算法, 视频修复, 运动矢量估计

Abstract: Traditional blotch detection algorithms obtain higher correct detection rates by reducing the value of threshold. However, the corresponding higher number of false alarms affects the following correction results directly. To maximize the ratio between correct detections and false alarms, this paper proposes an improved blotch detector based on simplified rank-ordered difference. The improved detector can achieve the most appropriate threshold to the different blotch in a certain frame by introducing dual-steps adaptive multi-threshold. It uses employment of texture matching to avoid the possible deviation caused by motion vector estimation in the regions with blotches. Performance evaluation is taken to the image sequences with both real blotches and artificially corrupted ones separately. Experimental results indicate higher correct detection rates and fewer false alarms simultaneously.

Key words: blotch detection, adaptive multi-threshold, texture matching, iterative algorithm, video restoration, motion vector estimation

中图分类号: 

• TP18