Sonar Image Target Detection And Tracking Based On Multi-resolution Analysis

With development of ocean resource exploitation and ocean engineer, the sonar need multi-resolution image and target recognition ability and multi-sonar matching and recognize ability besides of working at extremeness environment in order to requirement of high resolution terrain relief measurement and small target detection. Due to sonar equipment imaging no linearity and complexity of under water sound field environment, the background noise of sonar image include enough gray levels and the target area gray levels is comparatively less. The characters bring difficulty for following sonar image target detection and orientation track. Multi-resolution analysis tool can multi-scale details analysis by basis function expansion, translation and other computing, and it can effectively extract information from signals. At present, Multi-resolution analysis is international acknowledged advanced technology in the domain of information and signal processing. Meanwhile it is the front a question for discussion and study hotspot. More and more people attach importance to the application of multi-resolution analysis in the domains such as signal filtering, image denoising, image segmentation and image recognition etc.Multi-resolution analysis and its application in 2D sonar image and 3D sonar sequence processing are investigated in detail in this dissertation. The main work can be summarized on sonar image denoising, image area and movement target division, target and sensitivity area character distill, target tracking and orientation and multi-sonar scenes target matching etc.Firstly, the concepts and denoising methods in common use multi-resolution transform are recapitulative introduced and analyzed. At the same time, the imaging mechanism and the statistics characteristic of underwater acoustic image is expatiated. Through studying acoustic image of character which is bad contrast and deteriorates edges and detail, three the acoustic image denosing methods based on multi-resolution analysis are proposed. They are Sonar image denoising method based on sample matrix and Surfacelet transform, block adaptive denoising method of acoustical imaging and the sonar image denoising method based on 3D context model respectively. These methods are characterized by multi-direction option, parallel information processing, high efficiency of information using at air space and time space, and fusing the enhanced on multi-resolution. By the simulation results, the effectiveness and superiority of the methods are proved.Secondly, the classical image segmentation methods are recapitulative introduced and analyzed. Aim to character of mass random noise and target area edge blur of multi-resolution sonar image, which is recognized and restored based on multi-resolution and edge detection. The sonar image segmentation arithmetic is proposed based on spatial filter and Surfacelet transform edge detection. By the simulation results, the effectiveness and superiority of the methods are proved. It can obtain good segmentation result than MRF model segmentation and Wavelet clustering segmentation and protect edge and detail and improve visual effect.Thirdly, the classical movement target tracking methods based on image and image sequence are recapitulative introduced and analyzed. Aim to character of sonar image, the movement target tracking arithmetic based on LIP model and light flow, the sonar image sequence movement target tracking arithmetic based on Surfacelet transform at complex background, the image sequence movement target tracking arithmetic based on changeable stencil and Surfacelet transform are proposed. The more exact result is obtained the image sequence movement target tracking arithmetic based on changeable stencil and Surfacelet transform than mean shift track arithmetic. Under conditions of matching steady, it can take full use of scale fixedness character to estimate scale change, but mean shift track arithmetic can not efficiently estimate target scale and rotate value.Finally, the classical multi-cameras image matching methods are recapitulative introduced and analyzed. Aim to sonar image character, the sonar target matching arithmetic based on area SIFT description and Surfacelet transform according to sensitivity character to image different space frequency and vary areas of human eye system. The experimental results show that the arithmetic can efficiency distill sonar image target SIFT description character and realize target matching at multi-sonar scene. Its compute complexity is lower and matching precision is higher than whole application SIFT description.In conclusion, on the base of multi resolution analysis, this paper had researched on multi resolution analysis and its application in 2D sonar image and 3D sonar sequence processing. Aiming at the shortcoming of the region, the improved algorithms were proposed. Experimental results indicated that the adopted intelligent optimization algorithms and the proposed methods could attain good results.