Research And Implementation Of Auto-focus Method Based On Image Technology

Auto-focus has being an important function in all kind of imaging systems, it has widely application in many fields. In our country, the research and development about auto-focus is poor, but we are facing kinds of application requirement. The image processing is a technology developing rapidly, it promotes the development of auto-focus technology greatly, and numeralization and intelligentization has being a tendence of auto-focus technology. For these conditions, providing an auto-focus means based on image processing technology will have important significance.The auto-focus means based on image technology is different from those traditional auto-focus means entirely. The traditional ones must depend on some special assistant equipments, they uses these equipments to measure distance or find focus and realize auto-focus. However, the auto-focus based on image technology is completed by image quality analysis, it can judge the imaging state from the current image quality, then the system can adjust focus distance correctly supervised by imaging state. From the work flow, we know the image quality analysis is the key technology. In the thesis, three image quality analysis methods are presented detailedly:(1) The first one is the image quality analysis based on image contrast, it analyzes kinds of functions working at temporal field, frequency field and information entropy, compares their performance in the number of calculation and the time consumption of calculation, and finds out two better functions.(2) The next one is the image quality analysis based on image power spectrum, it supposes nature scenes have the same power spectrum, embeds a human vision system and includes a Winner de-noise filter. It analyzes a picture and gets an IQM (Image Quality Measure) value, the IQM value is highly relative to the estimation result through human vision system.(3) The last one is the image quality analysis based on wavelet analysis and neural network, it analyzes image from different frequency resolution through wavelet theory, and abstract the image characteristics from these detail information through statistics analysis, then uses an artificial neural network for quality pattern recognition. The recognition rate of this means is good.The realization of auto-focus, for contrast means, is similar with the 1-demension search, calculates the auto-focus function value, compares it with the previous one and decides the next position; for power spectrum or wavelet means, moves a special distance relative to the image quality level directly.Depending on above auto-focus theories, design an auto-focus system, analyze its performance and present the design of hardware and software particularly, the system is constructed by high speed DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array).