Xiao Mingxia

Study on monitoring technology of UAV aerial image enhancement for burning straw

One of the important factors of air pollution is straw burning. It is a good method to use unmanned aerial vehicle(UAV) image to monitor straw burning. But the UAV aerial image quality will be deteriorated by the suspended particles produced by straw incineration. In order to solve this problem, a new image enhancement algorithm is proposed. Based on the traditional single image dehazing method, the large gray area of image is detected through histogram. Then, the area to obtain modified coefficients is calculated and the dark channel prior algorithm is corrected by it. Finally Adaptive contrast enhancement is used to improve the quality of aerial image. The experimental results show that the new method achieves good image quality of fog environment and low luminance environment. It has better practical value in the field of aerial image recognition.

Multi-frequency periodic weak signal detection based on single-well potential stochastic resonance

Noise can be used by the stochastic resonance system to enhance the ability of weak signal detection. Based on classic stochastic resonance (SR) it can get good results but also can bring the problem of that its hard to find the optimal parameters of the system at the same time. Single-well potential stochastic resonance (SSR) was used in this paper to detect weak signals. SSR has only one parameter to be adjusted. It is easier to adjust the system to get the best state. This paper takes cross correlation coefficient as the measurement index on the basis of single-well potential stochastic resonance, detects multi-frequency periodic weak signal from the test signal after find the optimal parameter of the system with self-adapting method.