(Retracted) Method of defogging unmanned aerial vehicle images based on intelligent manufacturing

Abstract

Intelligent manufacturing is a major trend in manufacturing innovation around the world, and it is also the main direction and key breakthrough point for the transformation and upgrading of the manufacturing industry for a long time now and in the future. Here, we mainly study the role of intelligent manufacturing in defogging unmanned aerial vehicle (UAV) images and how to analyze UAV image defogging methods based on intelligent manufacturing. In recent years, with the continuous progress of UAV technology, UAV project has also been booming. Aerial photographing is one of the most widely used functions of UAV at present. However, when photographing images in severe weather environment such as haze, it will be affected by the absorption and scattering of light by a variety of different suspended substances in the environment, resulting in poor imaging quality, color distortion, fine pitch blur, and other adverse effects. For this reason, there is a large amount of research on the image haze removal of UAV in China. At present, the mainstream methods are based on non-vision sensor and physical model. However, due to the lack of haze removal effect and severe condition limitation in the practical application of the above methods, we explore an innovative set of automatic estimation haze removal method of atmospheric light based on this method, taking the principle of atmospheric estimation direction as the main research direction, and then through the steps of setting the global transmittance, calculating the atmospheric light amplitude, adjusting the image size, and automatically modifying the image condition threshold value, etc. The man–machine image is haze removal. To compare the advantages and disadvantages of the three methods, we choose standard deviation, information entropy, and objective evaluation method to analyze the results of the three methods. Data analysis shows that among the three haze removal methods, the atmospheric light automatic estimation haze removal method has greatly improved the overall haze removal effect. Compared with the previous two kinds of haze removal imaging in the haze environment, it can better guarantee the color balance degree, and also retain more image information, which makes the imaging clarity have a significant improvement, and the overall effect is more natural. This method has played a very good complementary role to the domestic UAV demisting technology.