Real-time video fogging camera technology introduction and advantages analysis

The droplets and solid particles in the air not only endanger human health, cause haze and lead to multiple traffic accidents, but also significantly reduce the quality of outdoor surveillance video. In hazy weather, the image appears dull and the contrast is low. The details of some important targets are submerged in the fog and difficult to observe. The practicality of the video surveillance system is greatly affected. Removing the fog in the video and improving the image quality have become an increasingly important technology to enhance the application value of outdoor video surveillance systems.

Real-time video fog technology introduction

At present, the fogging algorithm can be roughly divided into two categories: First, non-model image enhancement methods, which can meet the subjective vision requirements by enhancing the contrast of the images to achieve clarity; the other is a model-based image restoration method. Examine the causes of image degradation, model the degradation process, and use reverse processing to finally solve the problem of image restoration.

It is applied to all kinds of complex scenes, bad weather, all-weather real-time monitoring puts forward more stringent requirements on product portability and power consumption, processing effects, processing adaptability and so on. Good video fogging technology should combine the technical advantages of image enhancement and restoration on the basis of the atmospheric transmission model, so as to obtain a more ideal image effect and be quoted by practical engineering.

After fully analyzing the advantages and disadvantages of the fogging theory and conducting in-depth research and exploration, our researchers have developed a method based on the principle of atmospheric optics to distinguish the depth of field and fog in different areas of the image by combining the special requirements of video fogging in the field of security monitoring. The concentration is filtered to obtain an accurate and natural real-time video fogging technique for fog-free images. This technology can automatically adjust according to the change of fog conditions to adapt to various application scenarios, to avoid the effect of close-range fogging and over-ambiguity. At the same time, the efficiency and complexity of the implementation are taken into account, and the real-time performance of the entire fog is ensured. Can be engineered. At the same time, the technology can effectively remove the effects of fog and avoid the unrealisticness caused by color errors and excessive fog removal caused by over-processing of certain scenes.

Real-time video fogging technology advantages

The main advantages of real-time video fogging compared to other fogging methods are the following:

1. Fog penetration capability: Real-time video fogging technology can accurately remove the corresponding degree of fog according to different depth of field. The image enhancement method may have a better close-range fogging effect and the vision still has a lot of fogging problems. The fogging effect based on the image restoration method is related to the accuracy of the selected component. If the composition is selected accurately, the fogging effect is good. If the component selection is inaccurate, a very bad result may occur, so the performance of the fogging algorithm is not stable enough;

2. Permeability: The image after real-time video fogging is transparent and has good contrast. In other methods, fog is left over due to the accuracy of the depth of field estimation, so that the image after the fog is not very transparent;

3, details of the degree of reservation: real-time video fogging technology contains special details to maintain details, so after the fog after the fog of the image can hide the details of the original information after the fog continued to maintain or even partially enhanced, which is difficult to achieve other methods;

4, color saturation and reduction: real-time video fog technology will not change the color tone of the image but to increase the saturation of its color, other methods of fog may be the problem of tone distortion;

5, will not cause image dark phenomenon: real-time video fog technology contains brightness enhancement performance, the resulting image will not appear dark phenomenon. Other methods may cause the problem of reduced contrast;

6, a wide range of applications: real-time video fog technology can also be used for fog-free image processing, to improve the contrast and saturation of the original image, while improving the transparency of the image, and play a role in improving the visual quality of the image.

Application of Real-time Video Fog Technology in Security Monitoring

Real-time video fogging technology can improve the quality of video surveillance from multiple perspectives. It is a fog-permeable technology that can be used for aerosol treatment of various weather conditions caused by aerosols; it is also an enhancement algorithm that can significantly increase the contrast of the image, make the image transparent and clear, and can significantly enhance the image. Detail information, so that the original details of the hidden images are fully displayed; can improve the saturation of the image, so that the image is vivid, lively and vivid, the image after the fog treatment to maintain accurate hue, natural appearance, and thus get a good image Quality and visual experience.

Real-time video fogging technology has strong engineering capabilities. The technology can be applied to various resolutions including megapixel high-definition images; it can ensure real-time and accurate fogging under various resolutions; it can evaluate the current fog concentration in real time according to the target scene and adjust the fogging strength adaptively. Change the fog conditions of the scene without fear; the technology can obtain accurate depth of field information, and can accurately remove non-uniform fog in the same scene without residual haze.

The real-time video fogging function is initially implemented on some cameras and the actual collected fogging effect is achieved. In the details of the image, permeability, color and other aspects have significantly improved.

Real-time fogging technology can be combined with video compression and intelligent analysis technology to bring greater value to it. At present, the mainstream video compression algorithms are lossy compression, which will cause damage to the lower contrast details in the image, and the fog video generally has low contrast and less detail, and thus is often blurred and cannot be recovered after being encoded and compressed. The use of this technique can effectively enhance the contrast and details of the image, ensuring that valuable information is not lost in encoding and compression, and the effectiveness of information is significantly improved. Similar to the smart analysis, the real-time fogging technology processed images, the error rate of the analysis results, especially the false negative rate is significantly reduced, which greatly improves the practicality of the intelligent analysis system.

With the development of industry and the change of climate, haze has become a common weather phenomenon, which poses a great challenge to the quality of outdoor video surveillance applications. At present, in practical projects, radar, infrared, and other means are used to sense and monitor targets in hazy climates. Due to technical and cost constraints, there are no ideal solutions in the video field. The emergence of real-time video fogging technology can bring many values ​​to the field of video surveillance.

From the point of application of products and solutions, real-time video fogging technology can be applied to front-end cameras and domes to improve image quality in the field of security monitoring; it can be applied to DVRs to enhance the quality of images; Applies to large-screen displays to enhance their color saturation and image quality; can also be used in embedded client software to improve the quality of preview images.

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