基于模糊中值的IRFPA自适应盲元检测与补偿

红外焦平面阵列(IRFPA)的盲元既包括因材料与制造工艺的缺陷而导致的固定盲元,也包括因环境温度的漂移而出现的随机盲元.基于场景的盲元检测与补偿算法是去除这两种盲元,提高IRFPA 成像质量的有效手段.针对目前滤波类场景检测算法无法有效区分弱小点目标和随机盲元的缺陷,重点研究了随机盲元的响应特性和噪声特性,并提出了一种基于模糊中值与时域累积的盲元自适应检测与补偿算法.首先利用模糊中值滤波器从场景中提取出潜在的盲元,并通过多帧累积确定固定盲元和随机盲元的正确分布,最后对盲元进行实时补偿.实验结果证明:该算法可以有效地实现对盲元的校正,同时避免对弱小点目标的误判别.

Adaptive blind pixel detection and compensation for IRFPA based on fuzzy median filter

Blind pixels of IRFPA consist of fixed bad pixel and random bad pixel, the former is caused by material and manufacture defect, while the latter is mainly caused by temperature drift. Scene-based blind pixel detection and compensation algorithm is the effective method to eliminate these bad pixels and increase image quality. Aiming at the defect that the current filter-based detection methods can't distinguish random blind pixels and weak point targets, the response and noise feature of random blind pixels were first analyzed, and a new adaptive blind pixel detection and compensation algorithm based on fuzzy median and temporal accumulation was proposed. Fuzzy median filter was used to extract the potential blind pixels from scenes, then the exact distribution of fixed and random blind pixels were determined by temporal accumulation, and blind pixel compensation was performed finally. The experiments show that the proposed algorithm can effectively correct bad pixels while avoid misjudging weak point targets.