基于权值Gamma修正星空图像增强

Enhancement of Star Images based on Adaptive Gamma Correction with Weighting Distribution

电子倍增CCD(EMCCD)相机采集的星空图像动态范围大,背景亮度低,弱小目标与背景对比度低,因而不便于后期目标提取。文中采用基于权值的Gamma修正星空图像增强算法,首先利用直方图信息求出每个灰度的累计分布概率,然后将累计分布概率与Gamma修正算法结合起来,增强星空图像,提高弱小目标对比度。将文中算法与其他算法做实验比较,结果表明,该算法能有效增强星空图像。

It is difficult to extract dim target late in star Images because of the high dynamic range of star images caught by EMCCD camera,low brightness of background and low contrast of dim target. The paper proposes a method of enhancing star images based on adaptive gamma correction with weighting distribution. Firstly,we get cumulative distribution function from histogram. Then,combined with cumulative distribution function and Gamma correction algorithm,we enhance star images and improve the contrast of dim target. Compared with other algorithms,experimental results verify the effective performance of the proposed method to enhance star images.