Systematic errors in each link of the hyperspectral image chain degrade the data quality and the ability in subsequent application. In order to remove the systematic errors in hyperspctral radiance data, a cor-rection chain is established by taking the dispersive push-broom hyperspectral remote sensing system for an example. First, based on the image chain approach of hyperspectral sensors, the backgrounds and causes of re-sidual effects are presented. Then after the influence of each systematic residual effect and its applied detection and correction algorithm on hyperspectral data are analyzed and the relation between the individual processing is confirmed in proper sequence. Finally, the correction chain has been applied to the push-broom hyperspectral imager (PHI). Experimental results indicate that the visual effects are enhanced and the SNR is increased with 91.9% maximum, and the sharp peaks of reflectance spectra are eliminated, which approves that the correction chain can correct the remaining effects and improve the quality of hyperspectral data, as well as the ability in subsequent application.%高光谱遥感成像链路中各个环节产生的系统误差会降低数据质量（quality），从而削弱高光谱数据的应用潜力。为了消除高光谱辐亮度数据中的系统残余误差，以色散推扫型高光谱遥感系统为例，提出了基于成像链路的系统残余误差校正流程。首先，从成像链路出发，在不同环节分析系统残余误差的产生原因及机理；然后，通过分析检测及校正算法对数据质量的影响，以及误差项之间的内在联系，设计了一种系统残余误差校正流程；最后，以PHI高光谱数据作为数据源对提出的校正流程进行实验验证。结果表明：校正后的图像可视性增强；信噪比显著提高，最大提升值为91.9%；反射率数据中的过校正现象得到有效消除。利用该校正流程能够较好的消除数据中的系统误差，提高图像数据质量以及后续应用处理能力。
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