Background Clutter Suppression And Dim Target Detection Technology

The widespread applications in military and civil fields have made the detection and track of dim small moving targets with heavy clutter interference in image sequences a hot spot. Because the interested targets are inherently small or far away, and usually immersed in the strong background clutter, it is very difficult to detect and track them. This dissertation concentrates just in the two key techniques: the suppression of strong background clutter and the detection of the dim small moving targets in multi-frames.At first, this paper introduces and analyzes the issue of dim small moving targets detecting in image sequences in its typical applications, which are the imaging systems based on video, and presents the system of detecting dim small moving targets in image sequences based on the suppression of heavy background clutter. That is, a two-stage strategy is adopted that suppressing background clutter at first and then detecting targets based on multi-frame detection. And the tasks of clutter suppression are summarized as two points: one is removing background energy and improving SCNR, the other is transforming the complex, unknown distribution of original image data into a simple, known one. The evaluation technique of clutter suppression is discussed, and four engineering indices are suggested: the tests of Gaussian properties, the whitening characteristics, the SCNR gains and the detecting performance by single frame.Secondly, the technique of adaptive clutter estimation and suppression based on quasi-stationary sub-image partition is discussed and its computer simulations are completed. To overcome the global non-stationarity of the image in spatial domain, a method of partitioning original image into some quasi-stationary sub-block, in which adaptive filter is adopted for predicting and suppressing the background clutter, is presented. Because the method of partition, which is based on Quad-Tree Segmentation, is not precision enough, a method, which is based on Watershed Segmentation, is proposed. The raw image data processed by pre-smoothing as input data of adaptive filter can diminish background prediction distortion due to the spatial spread of the target. PC simulation and its results analysis are carried out. At last, the techniques for detecting dim small moving targets in image sequence are discussed. Several methods for small targets separating and detecting in the multi-frame detecting techniques are discussed in detail. To the problem, detecting dim small moving targets in the sequential images with strong background clutter interference, a scheme which is based on temporal integration of the tracks is presented.In a word, all the research works in this paper have important values both in theory and application on detecting and tracking dim moving targets in image sequences.