基于NSST的改进最大最小滤波与DCT-LSF的多聚焦图像融合

Multi-focus image fusion based on improved maximum and minimum filter and DCT-LSF

针对图像采集传感器的景深有限,导致采集图像的局部区域产生的失焦现象,本文提出了一种新的多聚焦图像融合算法。在NSST的框架下,对低频子带分解系数采用基于离散余弦变换(DCT)和局部空间频率(LSF)的融合规则;对高频子带分解系数则采用基于最大最小滤波结合平均滤波、中值滤波(MMAM)的融合规则;然后进行INSST重构获得融合图像。实验结果表明,与经典图像融合算法相比较,本文算法能有效融合图像的高低频子带信息,并在主客观评价方面都达到了较好的效果。

In view of the limited depth of field of the image acquisition sensor,which leads to the out-of-focus phenomenon in the local area of the acquired image,this paper proposes a new multi-focus image fusion algorithm.Under the framework of NSST,the fusion rules based on discrete cosine transform(DCT)and local spatial frequency(LSF)are used for the low-frequency sub-band decomposition coefficients,and the fusion rules based on the maximum and minimum filtering combined with average filtering and median filtering(MMAM)are used for the high-frequency sub-band decomposition coefficients;and then perform INSST reconstruction to obtain fused images.The experimental results show that,compared with the classical image fusion algorithm,the proposed algorithm can effectively fuse the high and low frequency sub-band information of the image,and achieves better results in both subjective and objective evaluation.