Research On A EIV-based Rational Function Model For Orthorectification Of Remote Sensing Imagery

Remote sensing image distortion commonly appears in images capturing process due to various factors, so image correction is necessary before the application of remote sensing images. A common image correction technique is orthorectification, and the Rational Function Model(RFM) is the most widely used othorectification technique. However, in the case of control point(RCP) with the error of heteroscedastic structure, a bias estimation is usually obtained by RFM.This research introduces EIV model to the process of RFM orthorectification based on previous research experiences. This approach could reduce the effects of control point errors on orthorectification and thus improve correction precision. Therefore, this paper proposes WTLS-based RFM orthorectification method, and its usability and effectiveness are verified by a series of experiments. The research contents include:1. Various factors affecting image distortion are summarized, and two correction models are introduced: geometric correction and orthorectification. The usability of both correction methods and their relationships are analyzed.2. Two RFM linearization methodsare analyzed andthe relationship of both methods is derived.3. Under the general conditions of the RCP with the error of heteroscedastic structure, this paper proposes WTLS-based RFM orthorectification method by introducing EIV model into RFM parameter estimation of WTLS estimation.4. A simulation experiment is performed to verify the advances of the proposed method on image orthorectification compared with the traditional method, two experiments of remote sensing images are performed to assess the usability and effectiveness of this proposed method on practical image orthorectification, the effects of quantity and quality of control points on the correction results is analyzed, the value of practical application of important results is concluded.