Imaging coordinate correction method based on matching error inhibition

Abstract

The invention discloses an imaging coordinate correction method based on matching error inhibition. The measurement image background area is manually marked, and matching point pairs are acquired; based on the matching point pairs, the iterative error method is utilized to model a geometric correction mapping matrix, and accuracy of the experimental result is improved; on the basis, the Euclideandistance and the threshold are utilized to detect and inhibit noise matching points; iterative error is reused to fit a new mapping matrix, and reference images are corrected; a measurement image is fused with an edge binary mask to acquire foot coordinates; the edge of a measurement image is fused with the reference images after geometric correction, and a foot-aligned reference image is acquiredthrough horizontal translation according to the foot point error. The method is advantaged in that the method is visual and effective, strong robustness is realized, the scene fitness is high, not only can a problem that imaging coordinates are affected by the background information, the complex structure miscellaneous information and the foot neighbor structure information in alignment calibration be solved, but also a problem of inconsistency of the fitting results of the multiple reference images can be solved.

Description

technical field [0001] The invention relates to the technical field of geometric correction, in particular to an imaging coordinate correction method based on matching error suppression. Background technique [0002] Geometric correction is error correction for geometric distortion. In practical applications, such as registration of multi-spectral and multi-temporal images, mapping of remote sensing images, and calibration of human bodies in the scene to solve the problem of height measurement, etc., due to the ambiguity of the image and the amount of calculation, the geometric correction The correctness faces many challenges. The commonly used image geometric correction methods include spatial transformation method and grayscale interpolation method. The imaging coordinate correction method based on matching error suppression generally does not require complex preprocessing of the image, but uses some statistical information of the image itself to measure the similarity of...

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Problems solved by technology

However, the method is complex, the scene adaptability is low, and the image outline is somewhat blurred

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