||Nowadays as people have higher awareness of public safety, different kinds of surveillance technologies emerge. Amongst these surveillance technologies, closed-circuit television (CCTV) and car video recorder are most frequently used by people, who simply want to honestly record the behaviors and acts of other people through images. However, surveillance system highly relies on sufficient light, so surveillance equipment seems ineffective in a low-light environment. But crimes and incidents commonly happen in the nighttime with poor visibility. Therefore, the algorithm for enhancement of nighttime image quality is extremely important. With a sound algorithm, unclear images obtained in an incident can be restored by image enhancement, and the truth can thus be known from clearer images, letting the victims receive fair treatment.|
It is known that image processing technique is established on a prerequisite of sufficient light. However, in times of practical application, the area of image processing is in lack of image enhancement technique to restore nighttime image. Taking the dehazing algorithm, dark channel prior (DCP) for example, although this method has remarkable effect in dehazing of daytime image, it is completely inapplicable to nighttime image. This is mainly because daytime scene or object has sunlight evenly shining on, so that the light amount received by the scene or object can combine with the physical model of atmospheric scattering to inversely derive the scene depth. Nevertheless, nighttime image has no sunlight to shine on, but is irradiated by intense and unstable artificial light (such as streetlamp, car light, and traffic lights), breaking the supposed prerequisite of DCP and disabling its direct application to nighttime image. The paper combines the image processing techniques of glow removal, DCP and color calibration in order to develop an effective method to enhance images in low-light environment.
Based on DCP algorithm , the paper uses negative film system and DCP’s dehazing feature to perform light compensation for the dark area of image, and employs this way to enhance low-light image. First of all, artificial light is removed; the area affected by artificial light is corrected; and the image is turned to be negative film. Using DCP, the paper calculates the scene depth and transmission of object, and uses guided image filtering to make transmission more refined. Through the physical model of atmospheric scattering, light is compensated for the image. Finally, the negative film of image is converted to be positive, and color calibration of image is carried out after compensation. Then the image in low-light environment is effectively enhanced.