基于快速有限剪切波变换与引导滤波的多聚焦图像融合算法

Multi-Focus Image Fusion Algorithm Based on Fast Finite Shearlet Transform and Guided Filter

为了使融合后的多聚焦图像细节特征丰富且边缘清晰,提出一种基于快速有限剪切波变换(FFST)与引导滤波的图像融合算法。利用FFST将源图像分解为低频系数和高频系数。在融合低频系数时,定义一种改进的拉普拉斯能量和(NSML),并设计一种基于区域NSML的低频系数选择方案;针对高频系数富含细节信息的特点,提出一种基于引导滤波的区域能量加权融合算法。然后,通过逆FFST获取最终的融合图像。对比实验结果表明,所提算法在主观视觉效果与客观评价指标方面都取得了较好的结果。

To preserve defined edges of the fused multi-focus image while enriching the detail features of the image, a novel algorithm based on the fast finite shearlet transform （FFST） and the guided filter is proposed. Firstly, the original images are decomposed into low frequency subband coefficients and bandpass direction subband coefficients by using FFST. Then, in the fusion of the low frequency coefficient, a novel Sum-Modified-Laplacian （NSML） is defined, and a selection scheme of low frequency coefficients is designed based on regional NSML. Due to the rich detail information of high frequency coefficient, we present a regional weighting energy fusion algorithm based on the guided filter. Finally, the final fused image is produced by inverse FFST. Comparison experiments are performed on different image sets, and experimental results demonstrate that the proposed algorithm performs better in both subjective and objective qualities.