A novel infrared moving target detection algorithm based on multiscale codebook model

Traditional target detection algorithm based on codebook model only use pixel information of video image while spatial scale information of image is ignored, so the detection result usually has high false detection rate and the target’s characteristics is not obvious. To overcome this difficulty, a novel infrared (IR) moving target detection algorithm based on multiscale codebook model is presented in this paper. The main principle of this algorithm is to make full use of image pixel information and scale information for moving target detection. First, by Gauss pyramid image hierarchical model, the IR video is stratified into three layers, namely the original layer, the second layer and the top layer. Second, background codebook model is built for each layer image, the main feature information is discovered to update background codebook models, and then moving target in IR video is detected according to the updated background model. Finally, the fusion operation is done on detection results of three layers to get the final detection result. Compared with traditional detection algorithm based on codebook model, this IR target detection algorithm combines image pixel information and scale characteristics. By using this novel algorithm, the experiments on some real world IR images are performed. The whole algorithm implementing processes and results are analyzed, and this novel detection algorithm is evaluated from the two aspects: subjective evaluation and objective evaluation. From the experiment results, we can see that the proposed method has better detection effects, richer target information and lower false detection rate.