Weak Target Detection Based On Morphology And Wavelet Transform

Detection of dim small moving targets in sequence images with complex clutter background is of vital importance to modern surveillance and alarm system, and it's hot all over the world.For long distance, the dim small moving target is usually composed of several pixels without specific shape and texture.And usually, the target is emerged in background clutter, which causes a lot of difficulties and challenges in detection.Firstly,the intensity features and motion features of the dim small moving target with complex clutter background are studied in this dissertation,and it's the basis for target detection.From the study on intensity features of the target, the dim small target in scene image presents as some special gray bubble, and the detection of the special bubble is the key task for target detection in a single image.The study on motion features of the target shows that, the motion of the moving target in sequence images has their independent motion and the track of the target is continuous. The detection of the independent motion and continuous track is the key task for motion detection of the target. On these grounds, a detecting system is designed in this dissertation,which includes target image pre-processing,target segmentation and target detection.This dissertation focuses on stduying the pre-processing algorithms of target image. The pre-processing algorithm is important in detecting target by enhancing the target and supressing noises,and it also can reduce the calculation and enhance the efficiency of detection. Two pre-processing algorithms about morphology and wavelet transform are mainly studied in this dissertation.For morphology pre-processing,the top-hat transform is adopted to enhance the target and remove the background.The selection of proper structure element is vital in the morphology,so a disk shape structure element is selected according to the intensity features of dim small target.And in wavelet transform pre-processing,the method of letting low frequency subband to zero and the method of letting high frequency subband multiply are mainly analyzed. In wavelet transform,the selection of base wavelet is important,so the biorthogonal wavelet is selected according to the image processing and target detection.In order to extract suspicious targets effectively and reduce the calculation,the adaptive threshold based on statistical mean and standard of image is adopted in target segmentation,and this threshold can adapt to more images with complex background.All the above work is just for a single frame image,and the intensity information of dim small targets is mainly used.But the real target can't be captured only by using the intensity features,because some false alarms exist,especially the target-like interfence. Therefor,the motion features of dim small targets in sequence images need to be used.So the continuity of track can be used to suppress the false alarms,then the real target can be captured and the track can be obtained.