Research On High Dynamic Range Image Acquisition Algorithm Based On Fused

With the continuous application and development of video surveillance technology, the image processing technology which is one of the indispensable video monitoring technologies is especially important.The dynamic range of light intensity is high in real scene, however ordinary image acquisition device, image processing device and image display device process generally 8 bit data, that is to say, whose dynamic range is low. When the dynamic range in real scene is more than the one which cameras can withstand, cameras can’t record all of light intensity information of real scene, due to the over exposure and the less exposure lead to the missing of the detail features of images and the distortion between the images which is displayed on machine and the images in real scene. In the forensic video monitoring, because of the sunshine indoor and people who is in indoor are not displayed at the same time, the information will be distorted in video monitoring technology. However, high dynamic range image is the key to solve this problem.At present, hardware production method and the software synthesis method are two kinds of main methods to obtain a high dynamic range image, which hardware production method is difficult to realize, software synthesis method comprises a radiation domain reconstruction method and the pixel domain direct synthesis method, the latter is more popular. This paper introduces the related technique of two kinds of software synthesis method. And the algorithm is simulated.For the above problem, based on the relevant literatures in home and abroad, in this paper, it introduce the algorithm about high dynamic range image fusion based on the detail feature.Whether or not the image is clear depends on its detail features, in this paper, firstly, he algorithm extracts the detail feature of low dynamic range images which is based on the self-adaption of pixels. Secondly, through choosing fusion criterion, the result reserves the pixels which contain rich information. In this way, we can gain one image which contains richer detail features and wider dynamic range. As camera response function is not required in the proposed algorithm, the computational load is not heavy. The final high dynamic range image can clearly be show in low dynamic range device. The application of the improved algorithm based on the pixel domain is more extensive.