为了得到更精确且信息更丰富的融合图像, 利用有限离散剪切波变换(FDST)改进了多聚焦图像融合算法。借助FDST完美的平移不变性和分解与重构过程中的快速有效性, 通过多尺度多方向分解来获取高低频子带系数, 然后对高频引入自适应加权与区域标准差匹配度法的融合策略, 并利用改进梯度投影的非负矩阵分解的融合手段处理低频子带, 分别得到融合后的高低频子带后, 采用FDST逆变换重构获得融合后的图像。对多聚焦图像的实验表明: 改进方法在主观视觉上图像清晰, 客观指标明显提高, 运行时间明显缩短, 充分说明了融合结果既保留了源图像丰富有效的信息, 又有很好的实效性。

To get a more accurate fusion image with richer information, the Finite Discrete Shearlet Transform (FDST) is used to improve the multi-focus image fusion algorithm. The perfect translation invariance of FDST and its high efficiency of decomposition and reconstruction are used to obtain the coefficient of high- and low- frequency sub-band by multi-scale and multi-direction decomposition. The fusion method of adaptive weighting used together with regional standard deviation matching is used for the high frequency, and the non-negative matrix factorization of improved gradient projection is used for the low frequency, then the high- and low-frequency sub-bands after fusion are obtained respectively. At last, the fusion image is reconstructed by FDST inverse transform. The experiments on multi-focus image show that, with the improved method, the fusion image is more distinct in subjective vision, has better objective indexes with shorter running time. The fusion result not only retains the rich and effective information of the source image, but also has a good effect.