Displacement vector detection method based on joint fractional Fourier transform and device

Abstract

The invention discloses a displacement vector detection method based on joint fractional Fourier transform. The method comprises the following steps: decomposing a video into single-frame images; determining a fractional order of Fourier transform, a reference image and a target image; placing the reference image and the target image on the two sides of an origin of a new coordinate system to form an input image; performing Fourier transform of the input image to obtain a Fourier transform frequency spectrum; performing square calculation to obtain a Fourier transform power spectrum of the input image; performing fractional Fourier transform of the power spectrum to obtain coordinates of cross-correlation peak of the target image; obtaining ideal outputs of coordinates of cross-correlation peak by the similarity method; and finally obtaining a displacement vector between the target image and the reference image. The invention also discloses a device for implementing the method. The method and the device achieve the arbitrary control on the cross-correlation peak position of the output plane based on the translation variability of the fractional Fourier transform, and achieve the diversify of the optical system structure according to the fractional order of the fractional Fourier transform.

Description

technical field [0001] The invention relates to the technical field of digital image stabilization methods, in particular to a detection method and detection device for a displacement vector based on a joint fractional Fourier transform correlator. Background technique [0002] With the development of human society towards high digitization, the rapid development and popularization of digital image, digital video and digital TV will become inevitable. Digital images may be subject to various degradations and distortions during the acquisition process, which inevitably leads to a decrease in resolution and blurred images. For example, in aerospace remote sensing imaging or ship-borne or vehicle-mounted imaging, due to the movement of the imaging device carrier, the relative motion between the imaging device and the imaging target will be caused, and the pixels will move chaotically on the image surface during the long exposure time, resulting in image loss. Blurring reduces ...

AI Technical Summary

Problems solved by technology

[0005] However, the displacement vector calculation based on the optical joint variable correlator has a relatively simple structure, which is a 4f system, that is, the input plane is located at the front focal plane of the lens, and the detection plane is located at the rear focal plane of the lens. When the distance between the reference image and the target image After the relative distance is fixed and the displacement vector between the two is determined, the distance between the cross-correlation peaks of the correlation output plane has been determined

If the relative distance or displacement vector between the reference image and the target image is too large, a pair of cross-correlation peaks may fall outside the field of view of the detection device

Similarly, if the distance between the reference image and the target image is too small or the displacement between them is too small, the cross-correlation peak may fall in the auto-correlation peak, so that the detection equipment cannot identify the cross-correlation peak, and thus cannot accurately detect out displacement vector

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