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《Optical Technique》 2005-03
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Study of edge detection method for noise-involved weak object based on stationary wavelet transform

ZHAO Dan-pei, WANG Yan-jie, LI Gui-ju(Department of Image Processing, Changchun Institute of Opitcs, Fine Mechanics and Physics, Changchun130031, China)  
A multi_scale method to detect image edges based on local modulus maxima of stationary wavelet transform was proposed for blurred image, low contrast image and Gauss noise_added image. The multi_scale edge detection effect of quadratic B_spline wavelet is validated. Throught the simulation, the three methods of local modulus maxima on wavelet were compared for capability of detection effect, anti_noise capacity and computation quantity. The contradiction between the edge detection precision and noise restraining ability was well resolved by applying a new method of adaptive threshold according to various backgrounds. This method can not only restrain noises but also extract the edge of weak object in allusion to low contrast image seriously polluted by noise. Experiments proved that this method with quadratic B_spline wavelet can effectively eliminate noise and accurately etract weak edge, resolved the problem of object detection for noise_invovlved image whose contrast is as low as 3%.
【CateGory Index】: TP391.41
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