基于光谱响应函数的ZY-3卫星图像融合算法研究

针对遥感影像融合过程中存在的光谱失真，提出了一种基于光谱响应函数（SRF）的ZY-3卫星影像融合算法，该算法通过研究亮度分量的模拟方法和空间细节注入方法，改进了传统的IHS算法。采用融合前后典型地物光谱曲线对比和无需参考图像的质量评价指标（QNR）两种方式对融合结果进行评价，发现该算法的光谱信息保持在89.94%，QNR值达0.75以上。结果表明，相对于其它IHS改进融合算法，基于ZY-3卫星传感器SRF的改进IHS融合算法无论在光谱信息保持还是空间信息增强方面都具有优势。

Study on ZY-3 Image Fusion Algorithms Based on Spectral Response Function

According to the problem of spectral distortion during remote sensed image fusion, the traditional IHS algorithm is improved by considering the methods of radiance component simulation and spatial detail injection based on spectral response functions (SRF) of ZY-3 satellite sensors. The fused images are evaluated by comparing spectral curves of typical ground features and utilizing a quality with no reference (QNR) index. Result shows that the new algorithm has a spectral fidelity of 89.94%, and its QNR value reaches up to 0.75. As a conclusion, compared with other improved algorithms based on IHS, the new IHS algorithm based on ZY-3 satellite sensors’ SRF has advantage of both spectral fidelity and spatial enhancement ability.