基于局部方向能量的鲁棒图像融合算法

针对现有小波类图像融合算法在特征表达上的不足，将对偶树复数小波变换引入图像融合中。Robins等的研究表明，局部能量对各类图像特征的表达和定位具有稳健性。基于对偶树复数小波变换，定义了局部方向能量和局部能量，结合人类视觉系统对图像特征的响应特性，定义了局部带限对比度，表达特征的显著性。实时图像融合系统中，输入可能被随机噪声污染。根据图像特征和噪声局部方向能量分布不同的特点，定义了局部方向能量熵，用以自适应改善带限对比度，提高融合过程对噪声的鲁棒性。对融合算法仿真结果的主客观性能分析，充分验证了本文提出的鲁棒的图像融合算法的卓越性能。

Local Orientation Energy Based Robust Image Fusion Algorithm

The dual-tree complex wavelet transform is employed in image fusion, to round the deficiencies of existing wavelet based algorithms in characteristics representation. The study of Robins et al.. shows that the local energy is robust in the representing and locating of all kinds of image features. Based on dual-tree complex wavelet transform, the local orientation energy and local energy are defined, which in conjunction with the response characteristic of human visual system to image features, the local banded contrast is finally formulated. In the real time image fusion system, inputs may be corrupted with random noises. The local orientation energy entropy is formulated, according to the different orientation energy distribution of features and noises, to modulate the local banded contrast adaptively. As a result, the robustness to noise is improved. The performance evaluations of the proposed algorithm both subjectively and objectively manifest the excel lent efficacy of the new scheme.