| 1. IntroductionThe gathering and the pretreatment of image is one of the most important technology of image process fields. The purpose that the image is gathered is to transforms the analogical image of the real world into a digital image, the key to this course lies in how to transform the analogical image into a digital image fast. And the purpose of the pretreatment is to improve SNR to stress the image characteristic through denoising processing. Image denoising includes space (time) and frequency domain methods. But their essence is to use the differences between noise and signal distributing in frequency domain, the signal is mainly distributing in low frequency part, while noise and image detail mainly in high frequency part. So there always is a difficulty needs to be solved, it's to eliminate random noise but not causing image edge blurring, to keep and increase image edge but not enlarge noise. The traditional low-pass filter method can restrain the high frequency part and decrease noise but may destroy image detail, and other methods also have other defects. How to construct a denoising algorithm which decreasing noise and keep image detail is always research object of scientists in image processing world. After the appearance of new signal processing tool—wavelet, the object can be implemented easily in reality. Wavelet analysis is a rapid developed new area of nowadays applied mathematics. Wavelet transform(WT) is space(time) and frequency local transform compared to Fourier transform and Windowed Fourier transform(Gabor transform). So it can pick-up local information from signal and can realize multi-analysis to signal by stretching , shrinking and shift etc. It solved many problems which can't be solved by Fourier transform. So we call wavelet transform as "mathematics microscope". Now wavelet transform is used widely in many areas. Especially in image processing area it shows great advantage and has promising future.2. The Hardware Design of Image Gathering SystemIn this paper, the author studied the structure of the picture gathering system at first, analysed the merit and demerit of different system. On this foundation, the author designed a real-timely picture gathering system. This system adopts the PHILIPS Company's high-speed video decode chip SAA7111 to perform A/D transition, used the integrated FPGA chip EP1K10TC144 of Altera Company as controlling the picture gathering, and the TMS320C6204 of TI Company was selected for data processing chip. Meanwhile, two SRAM of large capacity were used as the frame memories, and author adopted the ping-pong reading and writing mechanism to improving the speed of reading and writing memories. 3. Denoising AlgorithmThis emphasis of this paper's job concentrate on the research of image denoising algorithm. Author recommend the state of development of the denoising algorithm at present in signal processing field, especially image processing field. After the research of denoising algorithms in space(time) and frequency domain, the paper proposed a denoising algorithm in wavelet domain. Of all wavelet denoising algorithms, threshold-method is used the most usually. Threshold-method depends on the selection of threshold value and threshold function at great extent. The author studied the theories of selection of threshold value and threshold function in the course. Though threshold method can denoise effectually to some images, from universal significance, it can not do well, and have some limitation on using. So author looked for new denoising method, and found that proportion-shrinking method can remedy the demerit of threshold method through analysis to principle and examples of proportion-shrinking denoising algorithm. On it a new wavelet denoising algorithm--PCT was proposed by author, the experiment conclusion proves its adaptability and denoising effect far superior to threshold method and improved threshold method. The author established the base denoising research thought from different angles discussed above: noise-wavelet...
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