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Geometric accuracy of the remote sensing rectified image is usually evaluated by the root-mean-square errors (RMSEs) of theground control points (GCPs) and check points (CPs). These discrete geometric accuracy index data represent only on a localquality of the image with statistical methods. In addition, the traditional methods only evaluate the difference between the rectifiedimage and reference image, ignoring the degree of the original image distortion. A new method of geometric quality evaluation ofremote sensing image based on the information entropy is proposed in this paper. The information entropy, the amount ofinformation and the uncertainty interval of the image before and after rectification are deduced according to the information theory.Four kind of rectification model and seven situations of GCP distribution are applied on the remotely sensed imagery in theexperiments. The effective factors of the geometrical accuracy are analysed and the geometric qualities of the image are evaluated invarious situations. Results show that the proposed method can be used to evaluate the rectification model, the distribution model ofGCPs and the uncertainty of the remotely sensed imagery, and is an effective and objective assessment method

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

A New Method for Geometric Quality Evaluation of Remote Sensing Image Based on Information Entropy