{"title":"一种去除空间观测图像中高光目标污迹的算法","authors":"Jian Zhang, Liansheng Wang, Jian-Cun Ren","doi":"10.1109/ICACI.2012.6463358","DOIUrl":null,"url":null,"abstract":"Smear effect is a “fact of life” when using frame transfer type charge-coupled devices (CCDs) for image or video sequence acquisition. Usually, CCD smear effect can be decreased greatly by employing certain measures. But smear effect can seriously disturb the dim targets detection in Star Observation Image (SOI). In order to realize automatic removing highlight target's smear in SOI, an automatic de-smear system is established. Algorithms such as Gaussian noise distribution parameters estimation, smear detection and gray level correction etc. are investigated. First, Gaussian noise's distribution parameter of SOI is estimated with histogram least square curve fitting. Subsequently, utilizing smear features in observation image, a smear detection algorithm based on statistical information is proposed. Then, after the smear position is determined, contaminated pixel's gray level is corrected. Finally, a set of de-smear system in star observation image has been developed with Visual Studio 2005. Experimental results indicate that with the SOI of 16 Bits and 1024 pixels×1024 pixels, single frame image processing time is about 300 ms. Smear effects are well corrected. And useful information of stars and target has not been destroyed. The processed SOIs can satisfy the demands of stability, reliability and precision for dim target detection.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithm of removing highlight target's smear in space observation image\",\"authors\":\"Jian Zhang, Liansheng Wang, Jian-Cun Ren\",\"doi\":\"10.1109/ICACI.2012.6463358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smear effect is a “fact of life” when using frame transfer type charge-coupled devices (CCDs) for image or video sequence acquisition. Usually, CCD smear effect can be decreased greatly by employing certain measures. But smear effect can seriously disturb the dim targets detection in Star Observation Image (SOI). In order to realize automatic removing highlight target's smear in SOI, an automatic de-smear system is established. Algorithms such as Gaussian noise distribution parameters estimation, smear detection and gray level correction etc. are investigated. First, Gaussian noise's distribution parameter of SOI is estimated with histogram least square curve fitting. Subsequently, utilizing smear features in observation image, a smear detection algorithm based on statistical information is proposed. Then, after the smear position is determined, contaminated pixel's gray level is corrected. Finally, a set of de-smear system in star observation image has been developed with Visual Studio 2005. Experimental results indicate that with the SOI of 16 Bits and 1024 pixels×1024 pixels, single frame image processing time is about 300 ms. Smear effects are well corrected. And useful information of stars and target has not been destroyed. The processed SOIs can satisfy the demands of stability, reliability and precision for dim target detection.\",\"PeriodicalId\":404759,\"journal\":{\"name\":\"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACI.2012.6463358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACI.2012.6463358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
当使用帧传输型电荷耦合器件(ccd)进行图像或视频序列采集时,涂抹效应是一个“不可避免的事实”。通常情况下,采用一定的措施可以大大降低CCD的涂抹效应。但在恒星观测图像中,涂抹效应会严重干扰弱小目标的检测。为了实现SOI中高亮目标的自动去污,建立了一种自动去污系统。研究了高斯噪声分布参数估计、涂抹检测和灰度校正等算法。首先,利用直方图最小二乘曲线拟合估计SOI的高斯噪声分布参数;随后,利用观测图像中的涂片特征,提出了一种基于统计信息的涂片检测算法。然后,在确定涂抹位置后,对污染像素的灰度进行校正。最后,利用Visual Studio 2005开发了一套星观测图像去污系统。实验结果表明,在SOI为16 Bits, 1024 pixels×1024像素的情况下,单帧图像处理时间约为300 ms。涂抹效果得到了很好的纠正。而且有关恒星和目标的有用信息也没有被破坏。处理后的SOIs能够满足微弱目标检测的稳定性、可靠性和精度要求。
An algorithm of removing highlight target's smear in space observation image
Smear effect is a “fact of life” when using frame transfer type charge-coupled devices (CCDs) for image or video sequence acquisition. Usually, CCD smear effect can be decreased greatly by employing certain measures. But smear effect can seriously disturb the dim targets detection in Star Observation Image (SOI). In order to realize automatic removing highlight target's smear in SOI, an automatic de-smear system is established. Algorithms such as Gaussian noise distribution parameters estimation, smear detection and gray level correction etc. are investigated. First, Gaussian noise's distribution parameter of SOI is estimated with histogram least square curve fitting. Subsequently, utilizing smear features in observation image, a smear detection algorithm based on statistical information is proposed. Then, after the smear position is determined, contaminated pixel's gray level is corrected. Finally, a set of de-smear system in star observation image has been developed with Visual Studio 2005. Experimental results indicate that with the SOI of 16 Bits and 1024 pixels×1024 pixels, single frame image processing time is about 300 ms. Smear effects are well corrected. And useful information of stars and target has not been destroyed. The processed SOIs can satisfy the demands of stability, reliability and precision for dim target detection.