基于形态非抽样小波的实时图像融合方法

摘要

An efficient Morphological Un-Decimated Wavelet (MUDW) transform with more delicate and accurate multi-scale decomposition performance that suites real-time image fusion was proposed. It took the average of dilation and erosion as the analysis operator, and the difference of adjacent scale images as the detail image. Size-increasing structure elements were adopted to get better fusion result. Due to the simplicity of dilation and erosion operator, computation time is shorter than other real-time algorithms. Furthermore, a factor was added during reconstruction, to obtain an obvious enhancement effect. The experimental results show that the new method outperforms other real-time algorithms.%提出一种适合实时图像融合的形态非抽样小波(MUDW)变换,该变换采用膨胀和腐蚀操作的平均值作为分解过程中的分析算子,以相邻尺度图像之间的差作为细节图像,使尺度刻画更精细,细节描述更准确；采用随尺度增加而大小递增的结构元素,使尺度间差异更大,应用于图像融合可得到更好的图像融合效果.相比现有的实时图像融合方法,因为膨胀和腐蚀操作的便捷性,所以具有更高的实时性.通过实验证明了该方法具有良好的多尺度分解特性,取得了更好的融合效果；进一步在重构时设立增强因子能显著增强融合图像的效果.因此,在实时图像融合上具有较强的应用价值.