Target ranging method based on synthetic aperture focused images

Abstract

The invention discloses a target ranging method based on synthetic aperture focused images. The target ranging method disclosed by the invention comprises the following steps of: step 1, obtaining an equally-spaced line array camera position image sequence vertical to a target sight line by virtue of a small-hole imaging model camera, and taking a image of the camera position at the intersection point of a line array and a target sight line as a reference image; step 2, dividing a measurable distance range into a plurality of distance sections, and obtaining an aberration corrected and superposed image corresponding to each distance section, wherein each distance section is corresponding to one aberration corrected and superposed image; step 3, calculating the similarity between a neighbourhood area of each pixel in the reference image and a corresponding area in each aberration corrected and superposed image, and selecting the pixels as ranging pixels, wherein the changing ranges of the distances of the similarity of the pixels along with the aberration corrected and superposed images are greater than a preset threshold; and step 4, finding the distance section corresponding to the aberration corrected and superposed image with the maximum similarity, namely, the distance section in which target points corresponding to the ranging pixels are located. The target ranging method disclosed by the invention has the advantages of being low in realization cost, high in anti-interference capacity, simple in algorithm, and the like.

Description

technical field [0001] The invention relates to a ranging method, in particular to a target ranging method based on a synthetic aperture focusing image, and belongs to the technical field of surveying and mapping. Background technique [0002] There are many methods to measure the target distance, such as point ranging method based on laser pulse time difference, depth acquisition based on amplitude modulated wave phase difference, geometric optics focusing method, Moire topology technology, holographic interferometry, Fresnel diffraction technology and structured light law etc. Ultrasound is also commonly used to obtain depth information. Computer stereo vision technology has been widely used in many fields in recent years. The basic method is to observe the same scene from two or more viewpoints, obtain a set of images under different viewpoints, obtain the parallax between corresponding pixels in different images, and then measure the depth information of the target in ...

AI Technical Summary

Problems solved by technology

When the spatial three-dimensional scene is projected into a two-dimensional image, some useful information is lost due to the projection. The same scene will be very different in the image under different viewpoints. Affected by occlusion or shadow, several points of the scene may It does not appear in all images, and many changing factors in the scene, such as lighting conditions, noise interference, distortion of scene geometry, surface physical characteristics and camera characteristics, etc., are integrated into a single image gray value. It is very difficult to determine the above factors from this gray value, and this problem has not been well solved so far.

Increasing the baseline length can improve the accuracy of depth measurement, but at the same time it will increase the difference between images and increase the difficulty of matching

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