Research on Electronic Image Stabilization Technology of Vehicle-Mounted Remote-Controlled Weapon Station

The image information of the vehicle-mounted remote-controlled weapon station is jittered and blurred when the stance changes or vibrates, which increases the aiming difficulty and observation fatigue of the shooter, in order to realize the stable marching fire of the vehicle-mounted remote-controlled weapon station, the two-stage stable scheme with the shared gyro sensor is adopted in the system design, namely, the aiming device is rigidly fixed on the initially stable weapon platform, and then the electronic image stabilization is carried out. This paper proposes an approach combining two image stabilization schemes: gyro sensor data and image projection registration, optimizes the selection of image compensation data by registering and comparing the results of the two stable data, and uses the special features of the two schemes to improve the robust stability of electronic image stabilization, which ensure the observation effect of video image stabilization of the vehicle-mounted remote-controlled weapon station.

A New Defogging Algorithm for Underwater Images

Images taken underwater will appear greenish or blueish due to the scattering and attenuation of light, resulting in color distortion of underwater images. This paper proposes a new underwater image defogging algorithm, which can effectively remove image noise, improve the color saturation and contrast of underwater images, and restore clear underwater images without fog. The algorithm introduces guided filtering, which increases speed and work efficiency. The linear enhancement of the saturation component can effectively enhance the color saturation of the underwater image. Compensation for local brightness can better show image details. Through experimental comparison with other algorithms, our algorithm has achieved good advantages in terms of defogging, image structural information integrity, and resistance to color attenuation.

Image Motion Compensation Control Technology of Unmanned Aerial Vehicle (UAV) Airborne Photoelectric Reconnaissance Platform

Airborne photoelectric platform has a wide application prospect in the field of imaging, especially in the field of UAV reconnaissance. However, in the process of image acquisition, the photoelectric platform equipment will produce obvious image shift because of its own attitude change or speed instability, so it is necessary to compensate the collected image. In this study, when the image motion compensation is carried out, the internal and external parameters of the camera are adjusted, and the geometric model of the image is established. The Camera Calibration Toolbox provided by MatLab is used to calibrate the internal parameters of camera. At the same time, when obtaining the camera's internal parameters, the corresponding flight attitude angle is obtained with the aid of the inertial navigation system. At the same time of acquiring the attitude of the aircraft by hardware, it is necessary to obtain the image shift coefficient by using the function. The coordinate system needs to be transformed into a coordinate system suitable for the inertial navigation system, so as to facilitate the calculation of external parameters of the camera. The transformation matrix from image moving image to normal image can be established by obtaining the parameters inside and outside the camera. Through bilinear interpolation, the matrix is derived in MatLab environment. In the experiment, 16 black-and-white grid images are selected to obtain the attitude angle, so as to complete the calculation process of the conversion matrix. Then, the images with image shift are screened out from the images taken in aerial state. The method proposed in this study is used for image compensation. According to the root mean square error analysis, the image compensation scheme proposed in this study is helpful to the imaging application of UAV airborne platform.

Ghost-removal image warping for optical flow estimation

Traditional image warping methods used in optical flow estimation usually adopt simple interpolation strategies to obtain the warped images. But without considering the characteristic of occluded regions, the traditional methods may result in undesirable ghosting artifacts. To tackle this problem, in this paper we propose a novel image warping method to effectively remove ghosting artifacts. To be Specific, when given a warped image, the ghost regions are firstly discriminated using the optical flow information. Then, we use a new image compensation technique to eliminate the ghosting artifacts. The proposed method can avoid serious distortion in the warped images, therefore can prevent error propagation in the coarse-to-fine optical flow estimation schemes. Meanwhile, our approach can be easily integrated into various optical flow estimation methods. Experimental results on some popular datasets such as Flying Chairs and MPI-Sintel demonstrate that the proposed method can improve the performance of current optical flow estimation methods.