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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 .
Based on the analysis of the far-infrared image enhancement method based on imaging model proposed by Highnam and Brady, a new model-based adaptive enhancement algorithm for far infrared sequence image is designed and the influence of adaptive parameters on the performance of the algorithm Experimental research.The new algorithm can reflect the trade-off between quality enhancement and time enhancement by choosing appropriate adaptive parameters in order to meet different application requirements.