基于圖像處理技術(shù)的自動(dòng)調(diào)焦方法研究
[Abstract]:Image is an important carrier of information transmission. How to obtain clear and high-quality images has always been the direction and goal of people's exploration. Image quality is directly related to the subsequent image processing and application. Auto-focusing technology based on image processing is different from traditional focusing technology, which only relies on the acquired image information and does not require additional photoelectric detection equipment. Focusing process based on depth of focus method is a closed-loop control process, which integrates light, machine and electricity. It mainly includes three important links: the construction of focusing window, the selection of focusing evaluation function, and the feedback control of search algorithm for focusing motor. Based on the development status of focusing technology, a series of researches are carried out aiming at these three important links and combining with practical application. Firstly, the defocusing model of optical imaging system is established, the point spread function and optical transfer function under defocusing state are introduced, and the auto-focusing technology is established by analyzing the essential reasons of blurring image caused by defocusing. Secondly, focusing evaluation function is studied deeply. The selection of focusing evaluation algorithm is an important step in the focusing process. Defocusing will cause the loss of high-frequency components of the image, which will blur the edges and details of the image and degrade the image quality in the spatial domain. Fourier transform based image power spectrum has the characteristics of scene invariance and is widely used. Wavelet analysis overcomes the shortcomings of single Fourier resolution and has the characteristics of multi-resolution analysis. Wavelet power spectrum function is a power spectrum function based on Fourier transform. In order to verify the validity and universality of the proposed method, some experiments are carried out on LIVE database. At the same time, according to the characteristics of large-scale optical measurement equipment, a new method is proposed in this paper. The improved SML intelligibility evaluation function based on adaptive threshold segmentation adds two diagonal gradient values to the original SML function and takes the maximum value as the result of the point space filtering. The algorithm can effectively overcome the background noise and the influence of equipment jitter caused by atmospheric turbulence, and has high stability and sensitivity. Thirdly, the construction of the focusing window is studied. The influence of the size and position of the focusing window on the focusing evaluation curve is discussed. Due to the uncertainty of the position and size of the object observed by the optical measuring equipment, too large or too small of the window can easily cause the interference of background information or the loss of the object. Based on the limitation of the method, a window building method based on multi-scale pulse cosine transform is proposed. This method simulates the human visual attention mechanism and extracts the region of interest (ROI) of the image. The search strategy of the dynamic focusing system is the final realization of the focusing process.This paper improves the hill-climbing method which is commonly used and has high feasibility.The improved hill-climbing method is used as the basic search algorithm of the focusing system,and the wavelet power spectrum value of the image is used as the auxiliary means to judge the direction of the focusing search. Finally, according to the proposed focusing strategy, an embedded auto-focusing system based on DSP chip TMS320C6678 and Virtex-II series XC2V3000 is designed. A large number of experiments have been carried out on focusing accuracy, stability and real-time. The experimental results show that the auto-focusing method proposed in this paper is feasible and has high engineering application value.
【學(xué)位授予單位】:中國科學(xué)院研究生院(長春光學(xué)精密機(jī)械與物理研究所)
【學(xué)位級(jí)別】:博士
【學(xué)位授予年份】:2016
【分類號(hào)】:TP391.41
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