为获得到效果更好的融合图像,提出了一种基于结构相似度(SSIM)阈值自适应判定融合规则的改进算法.该算法对低频子带采用了基于相关系数离均差的加权求和融合算法,以保留更多的概貌信息;对高频子带则先计算待融合图像各个区域的SSIM,然后取平均值作为阈值,再根据各个区域的SSIM与阈值的关系自适应地选择高频子带融合算法,以保留更多的细节信息.实验结果表明,文中改进的图像融合算法可以获得细节更丰富和边缘更清晰的融合图像,融合图像质量的客观评价指标更优.
In order to obtain better fusion images, an improved algorithm on the basis of structural similarity (SSIM) threshold is proposed to determine fusion rules adaptively. In the algorithm, for low frequency sub-bands, a weighting summation fusion algorithm on the basis of correlation coefficient and deviation from mean is adopted to preserve more general information. For high frequency sub-bands, the SSIM of each region of the image to be fused is calcu-lated first and then the corresponding average value is taken as the threshold. Afterwards, a high frequency sub-band fusion algorithm is selected adaptively according to the relationship between the SSIM of each region and the threshold, so as to retain more detail information. Experimental results show that the improved image fusion algo-rithm helps achieve the fused images of richer detail, sharper edge and better objective evaluation index of quality.