Image processing method and device and electronic equipment

Abstract

The embodiment of the invention provides an image processing method and device and electronic equipment, and the method comprises the steps: obtaining at least two to-be-processed images, wherein theat least two images are images corresponding to at least two sub-bands in a scanning synthetic aperture radar ScanSAR image; correcting the proportion of the at least two images by utilizing the geographic position information of the images to obtain at least two corrected images; performing feature extraction on the at least two corrected images based on an ORB method to obtain a feature extraction result; splicing the at least two corrected images according to the feature extraction result. Thus, the proportion of the images is corrected according to the geographic information of the images,the corrected images are spliced based on the ORB method, and rapid and high-precision splicing of the images is achieved.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to an image processing method, device and electronic equipment. Background technique [0002] In related technologies, the scanning synthetic aperture radar (Scanning Synthetic Aperture Radar, ScanSAR) image stitching process usually uses the Scale Invariant Feature Transform (SIFT) algorithm, or the SURF (Speeded Up Robust Features) algorithm to extract features from the entire image points, and then match and filter all feature points to complete image stitching. In the case of ScanSAR image mapping bandwidth and large area, since the actual matching feature points are only points in the overlapping area, if the feature points are extracted from the entire image, a large number of redundant feature points will be generated in the non-overlapping area of ​​the image, which will consume matching Therefore, when using this type of method to stitch ScanSAR images, it will affe...

AI Technical Summary

Problems solved by technology

In the case of ScanSAR image mapping bandwidth and large area, since the actual matching feature points are only points in the overlapping area, if the feature points are extracted from the entire image, a large number of redundant feature points will be generated in the non-overlapping area of ​​the image, which will consume matching Therefore, when using this type of method to stitch ScanSAR images, it will affect the stitching speed, and the redundant feature points in the non-overlapping areas will also become interference factors, and mismatching may occur, resulting in a decrease in stitching accuracy

In addition, if the ORB (Oriented FAST and Rotated BRIEF) method is directly applied to the ScanSAR image, the ORB feature point extraction algorithm is affected by the ScanSAR image noise, and the quality of the extracted feature points is seriously degraded; the ORB feature point matching is affected by the quality of feature points and image deformation. , will lead to matching errors, which will lead to a decrease in splicing accuracy

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