Studies On Auto-focus System Based On Lifting DWT

Along with the progress of times, our need to each kind of digital equipments (such as digital camera, DV and image surveillance system and microscope etc.) increases day by day, and the research of auto-focusing also becomes more and more important. Auto-focusing is a key technique in the process of accessing digital pictures, it can make the digital equipments obtain a clear digital picture of the target object automatically. The degree of auto-focusing development directly influence the speed and quality of the digital equipments to get pictures, so the technique of auto-focusing is attached with significance.The current research of auto-focusing is always divide into two kinds:depth from defocus (DFD) and depth from focus (DFF). DFD obtains the focal depth of object target directly from defocus images, it moves the lens to the focused position with the calculation of the distance between lens and object target. DFF is established on the searching pattern, it moves the lens through the information get from the quality of several pictures. DFF is the essential direction of the research, and this text is also based on it.In this text, the principle of auto-focusing system is simply introduced first. Digital auto-focusing system first catches a picture of target object, then select only one small part of the picture as the auto-focusing region and use a focus measure function (FMF) to evaluate the image quality which determine how to move the lens to the focusing position. The auto-focusing system mainly includes three parts:the region of interest (ROI) selection, the focus measure function selection and the maximum searching algorithm selection. The three questions are respectively analyses in the contents behind.According to the analysis of key matters in auto-focus system, the text put forward a new strategy from the point of real-time and precision. Wavelet Transform is based on limited width basis function, it can analyze a signal through adjustable frequency that it can examine the gray changes at the picture edges. Compared with Fourier Transform and Cosine Transform, the Wavelet Transform can examine the picture quality more precisely. Lifting Wavelet Transform (the second generation DWT) divide the existing limited long filter and no longer rely on the Fourier Transform and the condition of translational and flexible. Compared with the first generation DWT. Lifting DWT inherit all the advantages of DWT and it can transform faster than the first generation DWT. According to the characteristics, the text compute the evaluation function through Lifting DWT.The improved auto-focus strategy put forward in the text first selects the ROI with PSO searching algorithm, then uses gradient evaluation function to evaluate the picture quality and searches the focused position with average searching algorithm by big steps. When find the small zone which the focused position lies on, change to use DWT evaluation function to evaluate the picture quality and search the focused position with mountain-climbing searching algorithm by small steps. In the course of the study, many experiments were carried out on the image sequence using the focusing strategy. The results show that, regardless of whether the object is in the center of the field, this strategy can achieve focusing precisely and the focusing time can be reduced30%-40%compared with the traditional wavelet algorithm. According to the experience results, the new auto-focus strategy can avoid the lens find the local focused positon, and it can decrease the time by searching the ROI automatically. The digital picture equipments can achieve auto-focused fastly and accurately with the new strategy.