现有技术不能保证获取图像时,对图像每个位置都具有同样的聚焦效果,这样便产生了多聚焦图像的融合问题,它包括如何进行多聚焦图像像素分类及采取何种融合决策。该文结合脉冲耦合神经网络(PCNN)模型和粗集理论,对该问题进行尝试性研究,提出了一种新的多聚焦图像融合算法。首先计算原始图像的清晰度,将清晰度矩阵送入PCNN进行处理,然后根据粗集理论对原图像像素进行分类处理,最后生成融合图像。仿真结果表明,该算法在一定程度上优于其他传统算法。且具有较好的抗噪性能。
A novel multi-focus image fusion algorithm is proposed for multi-focus image fusion. Pulse coupled neural network (PCNN) and rough set theory are employed to solve the problem of multi-focus image fusion. The clarity of original image is calculated and processed by PCNN. The original image pixels are classified based on rough set theory. Finally, a fusion image is created according to the classified results. Experiments indicate that the proposed method is superior to traditional algorithms with good anti-noise performance.