The Application Research Of Cell Image Edge Detection Using Wavelet

The edge information of cell image is very useful, which is the basis of cell image segment, it can affect the correctness of cell image recognition and analysis directly. Mostly, traditional arithmetic of image edge detection distill edge using gradient maximum or zero-crossing which base on gray discontinuousness on edge. They are affected easily by noise. Scale space filter can restrain noise and recognize edge reliably in big scale, and can confirm positions accurately in small scale, at last get the true positions of edge by focus processing from big scale to small scale. But traditional Canny arithmetic based on Guass scale space have shortcomings such as big computing and confirming positions inaccurately. Image edge detection based on multiresolution wavelet transform makes up these shortages before.Wavelet theory has good local inspect ability in time region and frequency region, and the character multiresolution. These are theory basis that wavelet transform is applied to cell image edge detection. In this paper, we define quadratic spline as wavelet, do the two dimentional dyadic wavelet transform on cell image, and get local modulus maxima from wavelet transform's results-modulus and angles, so we can find the cell image's edge image in each scales, at last, we compute optimum scale of cell image edge detection, and receive a good edge image which synthesize the characters in each scale. In this paper, we not only illustrate the superiority of quadratic spline wavelet edge detection's arithmetic from experimental work, but also prove quadratic spline wavelet is optimum edge detection's arithmetic based on Canny optimum criterions of edge detection.