Due to the existing limited dynamic range a camera cannot reveal all the details in a high-dynamic range scene. In order to solve this problem,this paper presents a multi-exposure fusion method for getting high qualit...Due to the existing limited dynamic range a camera cannot reveal all the details in a high-dynamic range scene. In order to solve this problem,this paper presents a multi-exposure fusion method for getting high quality images in high dynamic range scene. First,a set of multi-exposure images is obtained by multiple exposures in a same scene and their brightness condition is analyzed. Then,multi-exposure images under the same scene are decomposed using dual-tree complex wavelet transform( DT-CWT),and their low and high frequency components are obtained. Weight maps according to the brightness condition are assigned to the low components for fusion. Maximizing the region Sum Modified-Laplacian( SML) is adopted for high-frequency components fusing. Finally,the fused image is acquired by subjecting the low and high frequency coefficients to inverse DT-CWT.Experimental results show that the proposed approach generates high quality results with uniform distributed brightness and rich details. The proposed method is efficient and robust in varies scenes.展开更多
文摘预期失效分析方法(anticipatory failure determination,AFD)可以在产品实际发生问题之前预测产品的失效,并提出针对性的解决措施。传统AFD方法对功能失效事件的识别和情景推理主要依据基于经验的资源分析,分析结果的客观性和全面性较差,因此,将有限元分析(finite element analysis,FEA)方法引入AFD分析过程中,提出结合FEA和AFD的失效预测方法:在传统AFD流程基础上,建立了从操作流程和功能分析两个维度进行失效预测的过程模型;将TRIZ中功能模型作为功能失效分析的主要工具,提出了基于功能模型的5种失效相关事件的获取途径,并将FEA用于功能模型中涉及力作用的失效相关事件分析和后续情景推演中;针对失效预防问题,提出了基于失效场景树的失效消除的方法。将该方法用于钻杆接头的失效预测分析,构建了钻杆密封性失效的场景树,并给出了消除密封性失效的措施。
基金Supported by the National Natural Science Foundation of China(No.61308099,61304032)
文摘Due to the existing limited dynamic range a camera cannot reveal all the details in a high-dynamic range scene. In order to solve this problem,this paper presents a multi-exposure fusion method for getting high quality images in high dynamic range scene. First,a set of multi-exposure images is obtained by multiple exposures in a same scene and their brightness condition is analyzed. Then,multi-exposure images under the same scene are decomposed using dual-tree complex wavelet transform( DT-CWT),and their low and high frequency components are obtained. Weight maps according to the brightness condition are assigned to the low components for fusion. Maximizing the region Sum Modified-Laplacian( SML) is adopted for high-frequency components fusing. Finally,the fused image is acquired by subjecting the low and high frequency coefficients to inverse DT-CWT.Experimental results show that the proposed approach generates high quality results with uniform distributed brightness and rich details. The proposed method is efficient and robust in varies scenes.
