本文選題：新真空太陽望遠(yuǎn)鏡　切入點(diǎn)：太陽圖像重建　出處：《中國(guó)科學(xué)院研究生院(云南天文臺(tái))》2016年博士論文　論文類型：學(xué)位論文

【摘要】：深入研究太陽大氣活動(dòng)現(xiàn)象需要大視場(chǎng)、長(zhǎng)時(shí)間和多波段的高時(shí)空分辨率數(shù)據(jù)。目前地基大口徑太陽望遠(yuǎn)鏡都借助于自適應(yīng)光學(xué)技術(shù)和高分辨圖像重建技術(shù)實(shí)現(xiàn)太陽高空間分辨率成像觀測(cè)。高分辨圖像重建技術(shù)能有效克服湍流影響而實(shí)現(xiàn)目標(biāo)接近接近望遠(yuǎn)鏡衍射極限分辨率成像,相比自適應(yīng)光學(xué)技術(shù),它容易操作和實(shí)現(xiàn),但也因重建算法運(yùn)算耗時(shí)、重建流程繁瑣復(fù)雜而缺乏實(shí)時(shí)性。隨著一米新真空太陽望遠(yuǎn)鏡NVST在2010年建成和投入使用,國(guó)內(nèi)太陽觀測(cè)邁入高空間分辨率時(shí)代。NVST采用斑點(diǎn)重構(gòu)方法來處理每日觀測(cè)數(shù)據(jù),為能及時(shí)快速的處理海量觀測(cè)數(shù)據(jù),需有一套高效的重建策略和高速運(yùn)算的重建算法。本論文結(jié)合NVST實(shí)際觀測(cè),開展太陽高分辨高速重建算法的研究,研究?jī)?nèi)容包含NVST數(shù)據(jù)重建模式、重建算法優(yōu)化以及算法并行運(yùn)算等幾個(gè)方面。具體的研究細(xì)節(jié)和取得的相應(yīng)進(jìn)展如下:根據(jù)NVST實(shí)際觀測(cè)和數(shù)據(jù)處理現(xiàn)狀,確立了兩級(jí)數(shù)據(jù)處理模式Level1和Level1+,在斑點(diǎn)重構(gòu)算法比較耗時(shí)的大背景下,兩級(jí)處理模式讓NVST做到了數(shù)據(jù)及時(shí)發(fā)布。此外,在保證數(shù)據(jù)處理精度的前提下,對(duì)位移疊加法和斑點(diǎn)掩模法進(jìn)行了深入分析和優(yōu)化,對(duì)其中關(guān)鍵參數(shù)進(jìn)行了實(shí)驗(yàn)分析,最大限度地精簡(jiǎn)了運(yùn)算量,提高了觀測(cè)數(shù)據(jù)重建效率。在算法優(yōu)化的基礎(chǔ)上,采用硬件加速方式提高了高分辨重建算法的運(yùn)算速度。論述了高分辨重建算法中能夠并行計(jì)算的環(huán)節(jié),就高分辨重建算法在GPU和集群中并行加速進(jìn)行了實(shí)驗(yàn),在GPU中實(shí)現(xiàn)了準(zhǔn)實(shí)時(shí)的Level1級(jí)重建并實(shí)現(xiàn)了子塊圖像四維重譜并行計(jì)算;另外在集群中也實(shí)現(xiàn)了Level1和Level1+級(jí)快速重建。對(duì)NVST多通道數(shù)據(jù)的實(shí)際處理展開Level1和Level1+處理方法的應(yīng)用研究,并針對(duì)實(shí)際觀測(cè)和數(shù)據(jù)重建中遇到的問題給出解決方案。提出了一種重建中抑制光球通道s CMOS相機(jī)固定圖形噪聲的方法,通過對(duì)月亮Level1+級(jí)重建的結(jié)果看出,“二次平場(chǎng)”能有效抑制斑點(diǎn)掩模法中的固定圖形噪聲放大。在日面邊緣目標(biāo)的重建實(shí)驗(yàn)中,提出了一種改進(jìn)的互相關(guān)方法,該方法有效避免了相關(guān)極值誤差,保障了邊緣目標(biāo)高分辨重建的順利進(jìn)行。為提高色球數(shù)據(jù)重建結(jié)果的信噪比,采用并改進(jìn)了Level1重建算法,在改進(jìn)方法后,重建結(jié)果的分辨率大幅提高。
[Abstract]:A deep study of solar atmospheric activity requires a large field of view. Long time and multi-band high spatial and temporal resolution data. At present, the large aperture solar telescopes are based on adaptive optics technology and high resolution image reconstruction technology to realize the solar high spatial resolution imaging observation. High resolution image. The reconstruction technique can effectively overcome the influence of turbulence and achieve the target close to the telescope diffraction limit resolution imaging. Compared with adaptive optics, it is easy to operate and implement, but also because the reconstruction algorithm is time-consuming, the reconstruction process is complex and lack of real-time. With the new vacuum solar telescope NVST completed and put into use in 2010, In order to process large amount of observational data in time, NVST adopts speckle reconstruction method to process daily observation data in the era of high spatial resolution. It is necessary to have a set of high efficient reconstruction strategy and high speed reconstruction algorithm. This paper combines the actual observation of NVST and carries out the research of high resolution and high speed reconstruction algorithm of the sun. The research content includes the reconstruction mode of NVST data. The research details and corresponding progress are as follows: according to the actual observation and data processing status of NVST, the two-level data processing mode Level1 and Level1 are established. Under the background that the speckle reconstruction algorithm is time-consuming, the two-level processing mode enables NVST to release the data in time. In addition, the displacement superposition method and the speckle mask method are deeply analyzed and optimized under the premise of ensuring the accuracy of the data processing. The key parameters are analyzed experimentally, the computation is simplified to the maximum extent, and the efficiency of reconstruction of observation data is improved. On the basis of the optimization of the algorithm, Hardware acceleration is used to improve the speed of high resolution reconstruction algorithm. The parallel computation of high resolution reconstruction algorithm is discussed, and the parallel acceleration of high resolution reconstruction algorithm in GPU and cluster is tested. Quasi-real-time Level1 level reconstruction is realized in GPU and sub-block image four-dimensional respectral parallel computation is realized. In addition, Level1 and Level1 level fast reconstruction are also realized in cluster. The application of Level1 and Level1 processing methods to the practical processing of NVST multi-channel data is studied. According to the problems encountered in actual observation and data reconstruction, a method to suppress the fixed figure noise of the optical sphere channel s CMOS camera in reconstruction is proposed. The results of the Level1 reconstruction of the moon show that the "quadratic flat field" can effectively suppress the noise amplification of the fixed pattern in the speckle mask method. An improved cross-correlation method is proposed in the experiment of the reconstruction of the target on the edge of the solar plane. In order to improve the SNR of color sphere data reconstruction results, Level1 reconstruction algorithm is adopted and improved. The resolution of the reconstruction results is greatly improved.
【學(xué)位授予單位】：中國(guó)科學(xué)院研究生院(云南天文臺(tái))
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：P111.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 Chang-Hui Rao;Lei Zhu;Xue-Jun Rao;Lan-Qiang Zhang;Hua Bao;Xue-An Ma;Nai-Ting Gu;Chun-Lin Guan;Dong-Hong Chen;Cheng Wang;Jun Lin;Zen-Yu Jin;Zhong Liu;;First generation solar adaptive optics system for 1-m New Vacuum Solar Telescope at Fuxian Solar Observatory[J];Research in Astronomy and Astrophysics;2016年02期

2 施正;向永源;鄧輝;季凱帆;衛(wèi)守林;;一米真空太陽望遠(yuǎn)鏡Level 1級(jí)圖像選幀的GPU實(shí)現(xiàn)[J];科學(xué)通報(bào);2015年15期

3 Zhong Liu;Jun Xu;Bo-Zhong Gu;Sen Wang;Jian-Qi You;Long-Xiang Shen;Ru-Wei Lu;Zhen-Yu Jin;Lin-Fei Chen;Ke Lou;Zhi Li;Guang-Qian Liu;Zhi Xu;Chang-Hui Rao;Qi-Qian Hu;Ru-Feng Li;Hao-Wen Fu;Feng Wang;Men-Xian Bao;Ming-Chan Wu;Bo-Rong Zhang;;New vacuum solar telescope and observations with high resolution[J];Research in Astronomy and Astrophysics;2014年06期

4 劉長(zhǎng)玉;向永源;金振宇;;太陽色球圖像的選幀處理[J];天文研究與技術(shù);2014年02期

5 楊瀟;林鋼華;白先勇;朱小帥;;GPU計(jì)算在太陽物理中的應(yīng)用[J];科研信息化技術(shù)與應(yīng)用;2012年03期

6 劉忠;戴懿純;金振宇;邱耀輝;;斑點(diǎn)圖的重心與波前傾斜[J];天文研究與技術(shù);2009年02期

7 樓柯,劉忠,張瑞龍,盧汝為,吳銘蟾;紅外太陽塔撫仙湖老鷹地選址[J];天文學(xué)進(jìn)展;2001年02期

8 劉忠,邱耀輝,樓柯,盧汝為;斑點(diǎn)掩模法中的相位復(fù)原實(shí)施方法和像復(fù)原實(shí)驗(yàn)[J];光學(xué)學(xué)報(bào);1999年07期

9 劉忠,邱耀輝,樓柯,盧汝為;改正重譜中噪聲偏差的正性約束方法和天文高分辨率像復(fù)原實(shí)驗(yàn)[J];光學(xué)學(xué)報(bào);1999年02期

10 邱耀輝;呂瑞寧;錢蘋;仇樸章;劉忠;;斑點(diǎn)掩模法像復(fù)原天文實(shí)驗(yàn)初步結(jié)果[J];天文學(xué)報(bào);1992年03期

，

本文編號(hào)：1622756