隨機共振(Stochastic resonance)是一種利用增強噪音來達到信號增強的現象，目前廣泛運用在一維的信號處理上，經過許多學者研究下，此現象也可運用在二維的影像處理上。本文利用DSR-DWT演算法改善影像對比度，使得低對比度的影像，也能使用傳統的聚焦評價函數來計算聚焦平面，由本文研究結果可以得到，使用DSR-DWT演算法後的聚焦評價函數性能優於沒有使用DSR-DWT演算法。接著使用SSR法改善使用Sobel遮罩後的梯度影像作為邊緣偵測的演算法，此方法能增加邊緣偵測的效果。利用此邊緣偵測演算法與圓形霍氏轉換來做為粒子追蹤的演算法，實現直徑30~50μm微粒子自動聚焦、影像追蹤及推移。

Stochastic resonance is a phenomenon of enhancing the signal response by adding noise. Stochastic Resonance is widely used in 1-D signal processing. After researchers' dedicating to their study, they found that the phenomenon also can be applied to 2-D image processing. In this thesis, DSR-DWT (Dynamic stochastic resonator with discrete wavelet transform) method is used to enhance the contrast of the low contrast image such that the focus plane can be obtained by calculating conventional focus function. Results of present research revel that the focus quality by utilizing DSR-DWT method is better than not used. Then, SSR (Suprathreshold stochastic resonator) method is used to improve the gradient image by Sobel operator for edge detection. This approach can improve the performance of edge detection. The edge detection algorithm together with circular Hough transformation is employed for tracking moving micro-particle. The present research finally achieves the goal of auto-focusing, tracking and pushing the 30 to 50 μm micro-particle.

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