A real-time electronic image stabilization method based on flapping flight system

Abstract

The invention discloses a real-time electronic image stabilization method based on a flapping flight system. The method of the invention first uses the Harris corner detection algorithm and the KLT algorithm to solve the local motion vector of the inner corner of the image, and uses the least squares method to fit the global motion vector between adjacent frames; then, according to the characteristics of flapping flight, Savitzky- The combination of golay filtering and Kalman filtering extracts the motion parameters that need to be retained; then, the acceleration sensor is used to detect and determine the flight state of the flapping-wing aircraft, and the adjacent frame compensation algorithm or fixed frame compensation algorithm is adaptively selected to perform motion compensation on the image. Finally, a relatively stable video can be obtained by using the bilinear interpolation algorithm to enlarge the image and then crop the undefined part of the edge. The image stabilization algorithm is relatively simple and has good real-time performance, and can better solve the problem that the video captured by the camera system of the flapping aircraft is shaken due to the body shake during flight.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a real-time electronic image stabilization method based on a flapping-wing flight system. Background technique [0002] In recent years, domestic and foreign scholars and researchers have carried out a lot of research on bionic flapping-wing aircraft, and achieved certain achievements. The theory of aerodynamic performance of flapping-wing aircraft is more complicated than that of fixed-wing and rotary-wing aircraft. Especially at low Reynolds number, flapping-wing aircraft can make full use of unsteady aerodynamic characteristics to obtain higher lift. Under the same energy consumption, its endurance time and mileage can be longer, and it can be widely used in performances, aerial photography, Monitoring, mapping, disaster relief and other scenarios. [0003] Video images are one of the most important means for flapping-wing aircraft to navigate itself and obt...

AI Technical Summary

Problems solved by technology

Mechanical image stabilization is bulky and heavy, and is not suitable for low-load flapping-wing aircraft. Optical image stabilization is effective but expensive, and can only meet the anti-shake in specific directions. Electronic image stabilization technology is small in size and light in weight. , low energy consumption, low price, high portability, simple maintenance and easy upgrades and many other advantages have become the first choice for small aircraft, especially for flapping wing aircraft

[0005] Invention patent 202010328381.1 discloses a real-time electronic image stabilization method for video images under random jitter interference. The SURF algorithm is used to detect the feature points of the image, but the real-time performance of the algorithm is not high, and the feature point extraction ability for smooth-edged objects is relatively weak

After the radiation transformation is completed, the undefined blank areas that appear are not repaired, which affects the image stabilization effect

Invention patent 201710563620.X discloses an electronic image stabilization method based on improved KLT and Kalman filter, but does not give a specific method for image restoration. The effect achieved by cropping the edge of the image to complete the repair of the undefined area of ​​the image is not satisfactory

Invention patent 201810921737.5 discloses a real-time electronic image stabilization method for an underwater robot combined with the attitude information detected by the IMU unit to calculate the motion vector between image frames and perform image stabilization on the video, but the attitude information of the robot cannot fully represent the image There is a certain error in the information between frames. In addition, this method has extremely high requirements on the accuracy of the IMU, and the quality of image stabilization cannot be guaranteed.

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