基于复数小波域的多聚焦图像融合

A Multi-focus Image Fusion Algorithm in the Complex Wavelet Domain

提出了一种基于Q-shift双树复数小波变换的图像融合方法,该方法利用Q-shift双树复数小波变换对图像进行分解,根据低、高频系数相关性的特点,采用邻域梯度取大和"合成图像模值取大"相结合的融合方法对低、高频系数分别进行融合,并对高频融合结果进行"一致性"校验。实验表明,本文算法具有优于基于小波变换方法的性能。由于Q-shift双树复数小波近似的平移不变性和良好的方向选择性,因此能够有效地避免空间域融合算法存在的对比度低、块效应等问题以及基于小波变换融合算法存在的"伪影"和"振铃效应"。

The images are processed with Q-shift DT-CWT. The low frequency coefficients and high frequency coefficients are fused with NGMS （Neighborhood Gradient Maximum Selectivity） and SI-MVMS （Synthesis Image Module Value Maximum Selectivity） separately because of their different characteristics. For the low frequency coefficients, the ones having maximal neighborhood gradient are selected. For the high frequency coefficients, the ones having maximal absolute values are selected, and verify consistency of the fused coefficients . Experience results show that the images fused by the proposed algorithm are of better quality than that produced through the algorithms with wavelet transform. The proposed algorithm not only solves the problems such as low contrast and blocking effects caused by fusion algorithms in space domain, hut also avoids the artifacts and ringing artifacts exhibited by conventional wavelet based fusion algorithms, which benefit from the approximate shift invariant and good directional selectivity of Q-shift DT-CWT.