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Volume 37 Issue 4
May  2013
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Research of image processing method of far-field laser spots

  • Received Date: 2012-08-24
    Accepted Date: 2012-10-17
  • When processing far-field spot images with the commonly used laser spot image processing algorithm based on Gaussian beam characteristics, the data about lower energy is lost so that the processing accuracy of spot energy density at lower-end can not reach 0.01J/cm2 in demand. In order to get more accurate far-field laser spot data, an automatic threshold processing algorithm was proposed based on noise characteristics of the laser spot image. After analyzing the noise characteristics, the image extraction threshold was determined based on the 3 principles and the light spot image was processed. Experiments show that the algorithm can effectively restrain system noise, improve the light spot image processing quality, restore missing data information of the spot image, and make spot energy density low enough meet detection requirements. The results show that, the processing algorithm of light spot images based on the noise characteristics can effectively improve the processing accuracy of the far field laser facula, and is more suitable for the far field laser spot image processing.
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通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Research of image processing method of far-field laser spots

  • 1. 63889 Unit, Chinese People's Liberation Army, Mengzhou 454750, China;
  • 2. 63892 Unit, Chinese People's Liberation Army, Luoyang 471003, China;
  • 3. 63891 Unit, Chinese People's Liberation Army, Luoyang 471003, China

Abstract: When processing far-field spot images with the commonly used laser spot image processing algorithm based on Gaussian beam characteristics, the data about lower energy is lost so that the processing accuracy of spot energy density at lower-end can not reach 0.01J/cm2 in demand. In order to get more accurate far-field laser spot data, an automatic threshold processing algorithm was proposed based on noise characteristics of the laser spot image. After analyzing the noise characteristics, the image extraction threshold was determined based on the 3 principles and the light spot image was processed. Experiments show that the algorithm can effectively restrain system noise, improve the light spot image processing quality, restore missing data information of the spot image, and make spot energy density low enough meet detection requirements. The results show that, the processing algorithm of light spot images based on the noise characteristics can effectively improve the processing accuracy of the far field laser facula, and is more suitable for the far field laser spot image processing.

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