基于模型的远红外序列图像自适应增强算法及其分析

EnhancingFarInfraredImageSequenceswithModel BasedAdaptiveFiltering

在深入分析 Highnam和 Brady提出的基于成像模型的远红外图像增强方法的基础上 ,设计了一种新的基于模型的远红外序列图像自适应增强算法 ,并进行了自适应参数对算法性能影响的实验研究 .新算法可以通过适当选取自适应参数来体现对增强质量和增强时间的折衷考虑 ,以便满足不同的应用需求 .

Two enhancement algorithms, spatial and spatio temporal homomorphic filtering (SHF and STHF) were proposed by Highnam R et al in 1997 to enhance far infrared images based upon a far infrared imaging model. This paper proves that the enhanced results with SHF are in general smoother than those with STHF, although STHF may reduce the processing time greatly in comparison to SHF. Based on conclusion, an adaptive spatio temporal homomorphic filtering algorithm, ASTHF, is proposed. The adaptive factor of ASTHF is also discussed in detail to obtain the tradeoff between the smoothness and the convergence.