红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2014年
12期
4146-4152
,共7页
张闻文%刘婧婧%陈钱%顾国华
張聞文%劉婧婧%陳錢%顧國華
장문문%류청청%진전%고국화
电子倍增CCD%噪声分布模型%矩估计法%高斯-牛顿法%参数估计
電子倍增CCD%譟聲分佈模型%矩估計法%高斯-牛頓法%參數估計
전자배증CCD%조성분포모형%구고계법%고사-우돈법%삼수고계
EMCCD%noise distribution model%moment estimation method%Gauss-Newtow method%parameter estimation
为定量评价电子倍增CCD(EMCCD)图像噪声的大小,实现对EMCCD图像噪声参数的准确估计,研究了EMCCD的噪声分布模型及其参数估计方法。首先,讨论了EMCCD图像的噪声来源及其统计特性,由此建立了适于EMCCD的噪声分布模型。然后,提出了两种EMCCD噪声参数估计方法———矩估计法和高斯-牛顿法,采用Monte Carlo仿真验证其性能。仿真结果表明,矩估计法和高斯-牛顿法的平均相对误差和相对标准偏差均为10-2量级,估计精度较高,且高斯-牛顿法的估计精度要高于矩估计法。采集一系列无增益时积分时间为50 s的暗场图片和增益为50的本底图片,利用矩估计法和高斯-牛顿法分别估计出EMCCD的暗电流噪声、时钟感生电荷噪声和读出噪声,实验结果表明,估计值与EMCCD指标值一致,证明矩估计法和高斯-牛顿法能有效估计噪声参数且具有较高的精度。
為定量評價電子倍增CCD(EMCCD)圖像譟聲的大小,實現對EMCCD圖像譟聲參數的準確估計,研究瞭EMCCD的譟聲分佈模型及其參數估計方法。首先,討論瞭EMCCD圖像的譟聲來源及其統計特性,由此建立瞭適于EMCCD的譟聲分佈模型。然後,提齣瞭兩種EMCCD譟聲參數估計方法———矩估計法和高斯-牛頓法,採用Monte Carlo倣真驗證其性能。倣真結果錶明,矩估計法和高斯-牛頓法的平均相對誤差和相對標準偏差均為10-2量級,估計精度較高,且高斯-牛頓法的估計精度要高于矩估計法。採集一繫列無增益時積分時間為50 s的暗場圖片和增益為50的本底圖片,利用矩估計法和高斯-牛頓法分彆估計齣EMCCD的暗電流譟聲、時鐘感生電荷譟聲和讀齣譟聲,實驗結果錶明,估計值與EMCCD指標值一緻,證明矩估計法和高斯-牛頓法能有效估計譟聲參數且具有較高的精度。
위정량평개전자배증CCD(EMCCD)도상조성적대소,실현대EMCCD도상조성삼수적준학고계,연구료EMCCD적조성분포모형급기삼수고계방법。수선,토론료EMCCD도상적조성래원급기통계특성,유차건립료괄우EMCCD적조성분포모형。연후,제출료량충EMCCD조성삼수고계방법———구고계법화고사-우돈법,채용Monte Carlo방진험증기성능。방진결과표명,구고계법화고사-우돈법적평균상대오차화상대표준편차균위10-2량급,고계정도교고,차고사-우돈법적고계정도요고우구고계법。채집일계렬무증익시적분시간위50 s적암장도편화증익위50적본저도편,이용구고계법화고사-우돈법분별고계출EMCCD적암전류조성、시종감생전하조성화독출조성,실험결과표명,고계치여EMCCD지표치일치,증명구고계법화고사-우돈법능유효고계조성삼수차구유교고적정도。
In order to evaluate the size of image noise of electron multiplying CCD (EMCCD) quantitatively and achieve an accurate estimation of the EMCCD image noise parameters, the ECMMD noise distribution and its parameter estimation methods were studied. Firstly, the sources and statistical properties of EMCCD noise were discussed, and thereby an EMCCD noise distribution model was established. Then two EMCCD noise parameter estimation methods - - the moment estimation method and the Gauss -Newton method were proposed and Monte Carlo simulation was done to verify their performance. The results show that both the average relative error and the relative standard deviation of the two methods are of 10 -2 magnitude, presenting high estimation accuracy, and the Gauss- Newton method get better performance. With integration time of 50 s, a series of EMCCD images of the dark field with no gain and images of the background with gain of 50 were obtained. Using the moment estimation method and the Gauss- Newton method, the dark current noise, clock induced charge noise and readout noise were estimated. The results present that the estimated value is consistent with the EMCCD index value, which proves the moment estimation method and the Gauss- Newton method are able to estimate the noise parameter effectively and has a high accuracy.