光度测量图像智能阈值降噪方法

An Intelligent Threshold Noise Reduction Method for Images in Photometric Measurement

摘要:

为了提高光度测量精度,通过对光度测量过程中的入射散粒噪声、天光散粒噪声、暗电流散粒噪声、读出噪声的来源进行详细分析,有针对性地描述了降低各种噪声的方法,并针对暗电流散粒噪声与读出噪声及其他噪声残留提出了一种基于灰度直方图统计的智能阈值降噪方法；大幅消除了噪声对测量结果的影响,通过对恒星测光图像降噪前后光度计算结果的精度比对发现,采用这种方法将光度测量精度从原来的0.314 Mv提高到0.092 4 Mv,精度改善效果明显,并且解决了使用CCD测量光度结果不稳定的问题,具有较好的应用价值。

Abstract:

By analyzing the source of the incident shot noise, sky shot noise, dark-current shot noise, readout noise in the process of photometric measurements, it describe a method to reduce all kinds of these noise to improve accuracy of photometric measurement. Put forward an intelligent threshold noise reduction method for readout noise, dark-current shot noise and other residual noise. Substantially eliminate the impact of noise on the measurement results. Using stellar images before and after reducing the noise to calculate the photometric results, it can be seen that the method improved photometric accuracy from the original 0.314 Mv to 0.092 4Mv. It increases the accuracy of obvious effect and resolves instability problem of the photometric measurement using CCD.