CN106959161A - The method for eliminating atmospheric turbulance is realized using the compressed sensing broadband Hyperspectral imager based on directional scatter - Google Patents
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Abstract
一种利用基于随机光栅的压缩感知宽波段高光谱成像系统实现消除大气湍流的方法，包括以下步骤：获取基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵及采样数据；生成大气湍流传输矩阵；生成总体测量矩阵；重构多光谱图像；判断重构多光谱图像是否满足多光谱图像特性；修正大气湍流传输矩阵；生成总体测量矩阵；重构多光谱图像；判断重构多光谱图像是否满足多光谱图像特性；获取消除大气湍流影响的图像。本发明利用基于随机光栅的压缩感知宽波段高光谱成像系统信息获取效率较高、单次曝光获取宽波段上的光谱图像信息的特点，同时利用大气湍流在不同光谱的响应不同的特点，实现消除大气湍流的影响。
A method for eliminating atmospheric turbulence by using a random grating-based compressive sensing wide-band hyperspectral imaging system, comprising the following steps: acquiring a measurement matrix and sampling data of the random grating-based compressive sensing wide-band hyperspectral imaging system; generating atmospheric turbulent transmission matrix; generate the overall measurement matrix; reconstruct the multispectral image; judge whether the reconstructed multispectral image meets the characteristics of the multispectral image; modify the atmospheric turbulence transfer matrix; generate the overall measurement matrix; reconstruct the multispectral image; judge whether the reconstructed multispectral image Satisfy the characteristics of multispectral images; obtain images that eliminate the influence of atmospheric turbulence. The present invention utilizes the characteristics of high information acquisition efficiency of the compressed sensing wide-band hyperspectral imaging system based on random gratings, and the characteristics of obtaining spectral image information on a wide band with a single exposure, and at the same time utilizes the characteristics of different responses of atmospheric turbulence in different spectra to realize elimination The effect of atmospheric turbulence.
Description
技术领域technical field
本发明涉及消除大气湍流的方法，特别是一种利用基于随机光栅的压缩感知宽波段高光谱成像系统实现消除大气湍流的方法。The invention relates to a method for eliminating atmospheric turbulence, in particular to a method for eliminating atmospheric turbulence by using a compressed sensing wide-band hyperspectral imaging system based on random gratings.
背景技术Background technique
大气湍流是一种无规则涡旋运动现象，它的各个分量在时间和空间上表现出随机性。其中，大气湍流引起的振幅起伏导致光强闪烁现象，增加信号中的噪声，降低信噪比；大气湍流引起的相位起伏会严重破坏光波的时-空相干性，造成像点的弥散和抖动。因此，如何消除大气湍流的影响是大气成像技术领域亟需解决的问题。Atmospheric turbulence is a phenomenon of random vortex motion, and its components show randomness in time and space. Among them, the amplitude fluctuation caused by atmospheric turbulence leads to flickering of light intensity, increases the noise in the signal, and reduces the signal-to-noise ratio; the phase fluctuation caused by atmospheric turbulence will seriously destroy the time-space coherence of light waves, resulting in dispersion and jitter of image points. Therefore, how to eliminate the influence of atmospheric turbulence is an urgent problem in the field of atmospheric imaging technology.
为此，自上世纪五六十年代起，一系列成像技术提出并成功应用到空间探测中以消除大气湍流的影响。最为常见两种方法是散斑成像和自适应光学技术。散斑成像是一种通过对大量短曝光图像数据进行系综平均，而重建目标信息的图像后处理方法。其基本原理为：在物体短暂的曝光时间内，像面上的光强尚未进行平均累积，其中包含许多分辨率受限的细节，通过多次曝光采集，由计算机对大量图像数据进行Fourier变换、统计平均和反Fourier变换等处理，再现物体细节信息。计算处理包括图像Fourier变换模的反演和位相的恢复，结合获得模和位相进行Fourier反变换，最终重建物体图像。由于需要进行模和位相两步数据处理，因此所需计算量大，耗时长，图像的时效性不高。For this reason, since the 1950s and 1960s, a series of imaging technologies have been proposed and successfully applied to space detection to eliminate the influence of atmospheric turbulence. The two most common methods are speckle imaging and adaptive optics techniques. Speckle imaging is an image post-processing method that reconstructs target information by performing ensemble averaging on a large number of short-exposure image data. The basic principle is: during the short exposure time of the object, the light intensity on the image plane has not yet been averaged and accumulated, which contains many details with limited resolution. Through multiple exposures and acquisitions, the computer performs Fourier transformation on a large amount of image data, Statistical averaging and anti-Fourier transform processing to reproduce the detailed information of the object. The calculation process includes the inversion of the Fourier transform mode of the image and the recovery of the phase, combining the obtained mode and phase to perform the Fourier inverse transform, and finally reconstructing the object image. Due to the need for two-step data processing of mode and phase, the amount of calculation required is large and time-consuming, and the timeliness of the image is not high.
自适应光学是一种通过硬件消除大气湍流效应的技术。其主要由波前探测器、波前校正器和波前控制器三部分组成。自适应光学系统在工作时，需要已知的参照物(一般是比较明亮的恒星)。通过对参照星的探测，由波前探测器计算出大气湍流对波前的影响，常用的有空间光调制器，变形反射镜、薄膜反射镜等。由波前控制器对探测到信号进行分析处理，并控制波前校正器对波前进行修正。在对目标探测时，可以有效的消除大气湍流导致的波前扰动，获得高质量的图像。然而自适应光学系统制造困难，造价昂贵，功能复杂。Adaptive optics is a technology that removes the effects of atmospheric turbulence through hardware. It is mainly composed of three parts: wavefront detector, wavefront corrector and wavefront controller. When the adaptive optics system works, it needs a known reference object (usually a relatively bright star). Through the detection of the reference star, the influence of atmospheric turbulence on the wavefront is calculated by the wavefront detector. Commonly used are spatial light modulators, deformable mirrors, thin film mirrors, etc. The detected signal is analyzed and processed by the wavefront controller, and the wavefront corrector is controlled to correct the wavefront. When detecting targets, it can effectively eliminate wavefront disturbances caused by atmospheric turbulence and obtain high-quality images. However, the adaptive optics system is difficult to manufacture, expensive to manufacture, and has complex functions.
中科院上海光机所的韩生申研究组提出的基于随机光栅的压缩感知宽波段高光谱成像系统(专利号：ZL201410348475.X)能够单次曝光获得高空间分辨率和高光谱分辨率的从紫外光到中远红外光的宽波段光谱图像信息，为实现消除大气湍流的影响提供了新的硬件平台。The random grating-based compressive sensing broadband hyperspectral imaging system (Patent No.: ZL201410348475.X) proposed by Han Shengshen's research group at the Shanghai Institute of Optics and Mechanics, Chinese Academy of Sciences can obtain high spatial resolution and high spectral resolution from ultraviolet light to The wide-band spectral image information of mid- and far-infrared light provides a new hardware platform for eliminating the influence of atmospheric turbulence.
发明内容Contents of the invention
本发明的目的在于提出了一种利用基于随机光栅的压缩感知宽波段高光谱成像系统实现消除大气湍流的方法，利用大气湍流在不同光谱的响应不同以及多光谱图像的相似性、低峭度特性，结合硬件成像系统及软件重构算法，提供一种系统复杂度低、成本低的实现消除大气湍流的方法。The purpose of the present invention is to propose a method for eliminating atmospheric turbulence using a compressed sensing broadband hyperspectral imaging system based on random gratings, using the different responses of atmospheric turbulence in different spectra and the similarity and low kurtosis characteristics of multispectral images , combined with hardware imaging system and software reconstruction algorithm, provides a method for eliminating atmospheric turbulence with low system complexity and low cost.
本发明的基本思想是：预先标定基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵，通过基于随机光栅的压缩感知宽波段高光谱成像系统获得受到大气湍流影响的采样数据。通过选取不同的大气湍流结构常数，生成不同的大气湍流传输矩阵，并与预制的基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵相乘，生成总体测量矩阵。利用压缩感知算法和生成的总体测量矩阵，将基于随机光栅的压缩感知宽波段高光谱成像系统获取的采样数据重构为多光谱图像，并将多光谱图像的相似性、低峭度特性作为判断条件，选取出消除大气湍流影响的多光谱图像，合成为全色图像，获取消除大气湍流影响的图像。The basic idea of the present invention is to pre-calibrate the measurement matrix of the compressed sensing broadband hyperspectral imaging system based on random gratings, and obtain sampling data affected by atmospheric turbulence through the compressed sensing broadband hyperspectral imaging system based on random gratings. By selecting different atmospheric turbulence structure constants, different atmospheric turbulence transfer matrices are generated, and multiplied with the prefabricated stochastic grating-based compressive sensing broadband hyperspectral imaging system measurement matrix to generate an overall measurement matrix. Using the compressed sensing algorithm and the generated overall measurement matrix, the sampled data acquired by the compressed sensing broadband hyperspectral imaging system based on random gratings is reconstructed into a multispectral image, and the similarity and low kurtosis characteristics of the multispectral image are used as judgments Conditions, select the multispectral image that eliminates the influence of atmospheric turbulence, synthesize it into a panchromatic image, and obtain an image that eliminates the influence of atmospheric turbulence.
本发明的技术解决方案如下：Technical solution of the present invention is as follows:
步骤1、获取基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵及采样数据，具体是：Step 1. Obtain the measurement matrix and sampling data of the compressed sensing broadband hyperspectral imaging system based on random gratings, specifically:
S1.1.预先标定基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵；S1.1. Pre-calibrate the measurement matrix of the compressed sensing broadband hyperspectral imaging system based on random grating;
S1.2.利用基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据；S1.2. Use the compressed sensing broadband hyperspectral imaging system based on random grating to receive the sampling data affected by atmospheric turbulence;
步骤2、生成大气湍流传输矩阵，具体是：Step 2, generate the atmospheric turbulence transfer matrix, specifically:
S2.1.建立包含大气湍流结构常数、成像系统等效透镜焦距、波长及传播距离参数的大气湍流的光学传递函数；S2.1. Establish the optical transfer function of atmospheric turbulence including atmospheric turbulence structure constants, imaging system equivalent lens focal length, wavelength and propagation distance parameters;
S2.2.选取大气湍流结构常数的初始值，并获取基于随机光栅的压缩感知宽波段高光谱成像系统的等效透镜焦距、成像波段及传播距离的具体值；S2.2. Select the initial value of the atmospheric turbulence structure constant, and obtain the specific values of the equivalent lens focal length, imaging band and propagation distance of the compressed sensing broadband hyperspectral imaging system based on random gratings;
S2.3.对各个成像波段下的光学传递函数分别进行Fourier变换，按照矩阵对角方向排列生成大气湍流传输矩阵；S2.3. Perform Fourier transform on the optical transfer function under each imaging band, and generate the atmospheric turbulence transfer matrix according to the diagonal direction of the matrix;
步骤3、生成总体测量矩阵，具体是：Step 3, generate the overall measurement matrix, specifically:
将步骤1中获取的基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵与步骤2生成的大气湍流传输矩阵相乘，生成受大气湍流影响的总体测量矩阵；Multiply the measurement matrix of the random grating-based compressed sensing broadband hyperspectral imaging system obtained in step 1 with the atmospheric turbulence transfer matrix generated in step 2 to generate an overall measurement matrix affected by atmospheric turbulence;
步骤4、重构多光谱图像，具体是：Step 4, reconstructing the multispectral image, specifically:
利用压缩感知算法和步骤3生成的总体测量矩阵，将步骤1中的基于随机光栅的压缩感知宽波段高光谱成像系统受到大气湍流影响的采样数据重构为多光谱图像；Using the compressed sensing algorithm and the overall measurement matrix generated in step 3, reconstruct the sampling data affected by atmospheric turbulence in step 1 into a multispectral image;
步骤5、判断重构多光谱图像是否满足多光谱图像特性，具体是：Step 5, judging whether the reconstructed multispectral image satisfies the characteristics of the multispectral image, specifically:
判断步骤4的重构多光谱图像是否满足多光谱图像的相似性和低峭度特性，如果满足则进入步骤10，否则进入步骤6；Judging whether the reconstructed multispectral image in step 4 satisfies the similarity and low kurtosis characteristics of the multispectral image, if so, proceed to step 10, otherwise proceed to step 6;
步骤6、修正大气湍流传输矩阵，具体是：Step 6, correcting the atmospheric turbulent transfer matrix, specifically:
修正大气湍流的光学传递函数的大气湍流结构常数，再分别对各个波段下的光学传递函数进行Fourier变换，按照矩阵对角方向排列生成修正的大气湍流传输矩阵；Correct the atmospheric turbulence structure constant of the optical transfer function of atmospheric turbulence, and then perform Fourier transformation on the optical transfer function in each band, and generate the corrected atmospheric turbulence transfer matrix according to the matrix diagonal direction;
步骤7、生成总体测量矩阵，具体是：Step 7, generate an overall measurement matrix, specifically:
将步骤1中获取的基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵与步骤6修正的大气湍流传输矩阵相乘，生成受大气湍流影响的总体测量矩阵；Multiply the measurement matrix of the random grating-based compressed sensing broadband hyperspectral imaging system obtained in step 1 with the modified atmospheric turbulence transfer matrix in step 6 to generate an overall measurement matrix affected by atmospheric turbulence;
步骤8、重构多光谱图像，具体是：Step 8, reconstructing the multispectral image, specifically:
利用压缩感知算法和步骤7生成的总体测量矩阵，将步骤1中的基于随机光栅的压缩感知宽波段高光谱成像系统受到大气湍流影响的采样数据重构为多光谱图像；Using the compressed sensing algorithm and the overall measurement matrix generated in step 7, reconstruct the sampled data affected by atmospheric turbulence in the stochastic grating-based compressed sensing broadband hyperspectral imaging system in step 1 into a multispectral image;
步骤9、判断重构多光谱图像是否满足多光谱图像特性，具体是：Step 9, judging whether the reconstructed multispectral image satisfies the characteristics of the multispectral image, specifically:
判断重构步骤8的多光谱图像是否满足多光谱图像的相似性和低峭度特性，如果满足则进入步骤10，否则进入步骤6；Judging whether the multispectral image in the reconstruction step 8 satisfies the similarity and low kurtosis characteristics of the multispectral image, if so, proceed to step 10, otherwise proceed to step 6;
步骤10、获取消除大气湍流影响的图像，具体是：Step 10, obtain the image that eliminates the influence of atmospheric turbulence, specifically:
将重构的多光谱图像结果合成为全色图像，获取消除大气湍流影响的图像。Synthesize the reconstructed multispectral image results into a panchromatic image to obtain an image that eliminates the influence of atmospheric turbulence.
所述的步骤1获取基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵及采样数据，具体是：利用专利“压缩光谱成像系统测量矩阵的获取方法”(专利号：ZL201410161282.3)预先标定基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵；利用基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据；The above step 1 obtains the measurement matrix and sampling data of the compressed sensing broadband hyperspectral imaging system based on random grating, specifically: using the patent "method for obtaining measurement matrix of compressed spectral imaging system" (patent number: ZL201410161282.3) in advance Calibrate the measurement matrix of the compressed sensing broadband hyperspectral imaging system based on random gratings; use the compressed sensing broadband hyperspectral imaging system based on random gratings to receive sampling data affected by atmospheric turbulence;
所述的步骤2生成大气湍流传输矩阵，具体是：根据Kolmogrov和Obukhov发展的湍流统计理论，建立包含大气湍流结构常数、成像系统等效透镜焦距、波长及传播距离参数的大气湍流的光学传递函数；根据实际大气情况，以大气湍流结构常数的典型值作为其初始值，并将成像系统的等效透镜焦距及传播距离带入大气湍流的光学传递函数中，获取不同成像波段下的大气湍流的光学传递函数；对各个成像波段下的光学传递函数分别进行Fourier变换，结果按照矩阵对角方向排列，即是大气湍流传输矩阵；Described step 2 generates the atmospheric turbulent transfer matrix, specifically: according to the turbulent statistical theory developed by Kolmogrov and Obukhov, establishes the optical transfer function of the atmospheric turbulent including the atmospheric turbulent structure constant, the equivalent lens focal length of the imaging system, the wavelength and the propagation distance parameters ; According to the actual atmospheric conditions, the typical value of the atmospheric turbulence structure constant is taken as its initial value, and the equivalent lens focal length and propagation distance of the imaging system are brought into the optical transfer function of the atmospheric turbulence to obtain the atmospheric turbulence under different imaging bands Optical transfer function: Fourier transform is performed on the optical transfer function under each imaging band, and the results are arranged in the diagonal direction of the matrix, which is the atmospheric turbulence transfer matrix;
所述的步骤3生成总体测量矩阵，具体是：将步骤1中获取的基于随机光栅的压缩感知宽波段高光谱成像系统测量矩阵与步骤2生成的大气湍流传输矩阵相乘，结果即是受大气湍流影响的总体测量矩阵；The step 3 generates an overall measurement matrix, specifically: multiply the measurement matrix of the compressed sensing broadband hyperspectral imaging system based on random grating obtained in step 1 with the atmospheric turbulence transfer matrix generated in step 2, and the result is the atmospheric turbulence transmission matrix Overall measurement matrix for turbulence effects;
所述的步骤4重构多光谱图像，具体是：利用线性或非线性的压缩感知算法和步骤3生成的总体测量矩阵，将步骤1中的基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据重构为多光谱图像结果；The step 4 reconstructs the multispectral image, specifically: using the linear or nonlinear compressive sensing algorithm and the overall measurement matrix generated in step 3, the random grating-based compressive sensing broadband hyperspectral imaging system in step 1 receives Sampling data affected by atmospheric turbulence is reconstructed into multispectral image results;
所述的步骤5判断重构多光谱图像是否满足多光谱图像特性，具体是：不受大气湍流影响的多光谱图像满足相似性和低峭度特性，判断步骤4重构图像是否满足多光谱图像的相似性和低峭度特性，如果满足则进入步骤10获取消除大气湍流影响的图像，否则进入步骤6修正大气湍流传输矩阵；The step 5 judges whether the reconstructed multispectral image satisfies the characteristics of the multispectral image, specifically: the multispectral image not affected by atmospheric turbulence satisfies the similarity and low kurtosis characteristics, and judges whether the reconstructed image in step 4 satisfies the characteristics of the multispectral image The similarity and low kurtosis characteristics of , if it is satisfied, go to step 10 to obtain the image that eliminates the influence of atmospheric turbulence, otherwise go to step 6 to correct the atmospheric turbulence transfer matrix;
所述的步骤6修正大气湍流传输矩阵，具体是：修正大气湍流的大气湍流结构常数，并带入大气湍流的光学传递函数中，再对各个成像波长下的光学传递函数分别进行Fourier变换，结果按照矩阵对角方向排列，得到新的大气湍流传输矩阵，从而实现对大气湍流传输矩阵的修正；The step 6 corrects the atmospheric turbulence transfer matrix, specifically: correcting the atmospheric turbulence structure constant of the atmospheric turbulence, and bringing it into the optical transfer function of the atmospheric turbulence, and then performing Fourier transform on the optical transfer function at each imaging wavelength, the result Arranged according to the diagonal direction of the matrix, a new atmospheric turbulent transfer matrix is obtained, so as to realize the correction of the atmospheric turbulent transfer matrix;
所述的步骤7生成总体测量矩阵，具体是：将步骤1中获取的基于随机光栅的压缩感知宽波段高光谱成像系统测量矩阵与步骤6修正的大气湍流传输矩阵相乘，结果即是受大气湍流影响的总体测量矩阵；The step 7 generates an overall measurement matrix, specifically: multiply the random grating-based compressed sensing broadband hyperspectral imaging system measurement matrix obtained in step 1 with the atmospheric turbulence transfer matrix corrected in step 6, and the result is the atmospheric turbulence transmission matrix Overall measurement matrix for turbulence effects;
所述的步骤8重构多光谱图像，具体是：利用线性或非线性的压缩感知算法和步骤7生成的总体测量矩阵，将步骤1中的基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据重构为多光谱图像结果；The step 8 reconstructs the multispectral image, specifically: using the linear or nonlinear compressive sensing algorithm and the overall measurement matrix generated in step 7, the random grating-based compressive sensing broadband hyperspectral imaging system in step 1 receives Sampling data affected by atmospheric turbulence is reconstructed into multispectral image results;
所述的步骤9判断重构多光谱图像是否满足多光谱图像特性，具体是：不受大气湍流影响的多光谱图像满足相似性和低峭度特性，判断步骤8重构图像是否满足多光谱图像的相似性和低峭度特性，如果满足则进入步骤10获取消除大气湍流影响的图像，否则进入步骤6修正大气湍流传输矩阵；The step 9 judges whether the reconstructed multispectral image satisfies the characteristics of the multispectral image, specifically: the multispectral image not affected by atmospheric turbulence satisfies the similarity and low kurtosis characteristics, and judges whether the reconstructed image in step 8 satisfies the multispectral image The similarity and low kurtosis characteristics of , if it is satisfied, go to step 10 to obtain the image that eliminates the influence of atmospheric turbulence, otherwise go to step 6 to correct the atmospheric turbulence transfer matrix;
所述的步骤10获取消除大气湍流影响的图像，具体是：利用多波长图像合成技术，将重构的多光谱图像结果合成为全色图像，获取消除大气湍流影响的图像。The step 10 is to obtain an image that eliminates the influence of atmospheric turbulence, specifically: use multi-wavelength image synthesis technology to synthesize the reconstructed multispectral image into a panchromatic image, and obtain an image that eliminates the influence of atmospheric turbulence.
与现有技术相比，本发明的技术效果：Compared with prior art, technical effect of the present invention:
1)基于随机光栅的压缩感知宽波段高光谱成像系统单次曝光获得高空间分辨率和高光谱分辨率的从紫外光到中远红外光的宽波段光谱图像信息，利用大气湍流在不同光谱的响应不同以及多光谱图像的相似性和低峭度特性，实现消除大气湍流的影响。1) The compressive sensing wide-band hyperspectral imaging system based on random grating obtains high-spatial and high-spectral resolution wide-band spectral image information from ultraviolet light to mid-far infrared light with a single exposure, using the response of atmospheric turbulence in different spectra The similarity and low kurtosis characteristics of different and multispectral images realize the elimination of the influence of atmospheric turbulence.
2)结合硬件成像系统及软件重构算法，系统复杂度低、成本低的实现消除大气湍流影响的方法。2) Combining the hardware imaging system and software reconstruction algorithm, the method of eliminating the influence of atmospheric turbulence is achieved with low system complexity and low cost.
附图说明Description of drawings
图1为基于随机光栅的压缩感知宽波段高光谱成像系统。Figure 1 is a compressive sensing broadband hyperspectral imaging system based on random gratings.
图中标记如下：The markings in the figure are as follows:
1-前置成像系统 2-二向色滤波片 3-出瞳转换系统 4-随机光栅 5-光电探测器6-计算机 7-出瞳转换系统 8-随机光栅 9-光电探测器 10-放大成像系统 11-放大成像系统1-Pre-imaging system 2-Dichroic filter 3-Exit pupil conversion system 4-Random grating 5-Photodetector 6-Computer 7-Exit pupil conversion system 8-Random grating 9-Photodetector 10-Magnified imaging System 11 - Zoom Imaging System
①-物面 ②-前置成像系统出瞳 ③-第一成像面 ④-原始探测面 ⑤-第一成像面⑥-原始探测面①-Object plane ②-Exit pupil of front imaging system ③-First imaging surface ④-Original detection surface ⑤-First imaging surface ⑥-Original detection surface
图2为本发明利用基于随机光栅的压缩感知宽波段高光谱成像系统在长曝光时间下实现消除大气湍流的方法实施例流程图。FIG. 2 is a flow chart of an embodiment of a method for eliminating atmospheric turbulence under long exposure time using a compressed sensing broadband hyperspectral imaging system based on random gratings in the present invention.
具体实施方式detailed description
下面结合图2来说明本发明如何利用基于随机光栅的压缩感知宽波段高光谱成像系统实现消除大气湍流的。The following describes how the present invention eliminates atmospheric turbulence by using a random grating-based compressive sensing wide-band hyperspectral imaging system in conjunction with FIG. 2 .
如图2所示，首先利用专利“压缩光谱成像系统测量矩阵的获取方法”(专利号：ZL201410161282.3)预先标定基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵AGISC；利用基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据Y。As shown in Figure 2, first use the patent "Acquisition Method of Measurement Matrix of Compressed Spectral Imaging System" (Patent No.: ZL201410161282.3) to pre-calibrate the measurement matrix A GISC of the compressed sensing broadband hyperspectral imaging system based on random grating; The random grating compressive sensing broadband hyperspectral imaging system receives the sampling data Y affected by atmospheric turbulence.
根据Kolmogrov和Obukhov发展的湍流统计理论，建立长曝光时间下的大气湍流的光学传递函数为According to the statistical theory of turbulence developed by Kolmogrov and Obukhov, the optical transfer function of atmospheric turbulence under long exposure time is established as
其中f是透镜的焦距，λ是波长，是大气湍流结构常数，z是传播距离。已知大气湍流结构常数的典型值从1e-12(强湍流)到1e-18(弱湍流)，根据成像时的实际大气情况，选取某一典型值作为大气湍流结构常数的初始值，并将基于随机光栅的压缩感知宽波段高光谱成像系统的等效透镜焦距及传播距离带入公式(1)中，获取不同成像波段下的大气湍流的光学传递函数H(u；λi)；对各个成像波段下的光学传递函数公式(1)分别进行Fourier变换，结果按照矩阵对角方向排列，即是长曝光时间下的大气湍流传输矩阵where f is the focal length of the lens, λ is the wavelength, is the atmospheric turbulence structure constant, and z is the propagation distance. It is known that the typical value of the atmospheric turbulence structure constant is from 1e -12 (strong turbulence) to 1e -18 (weak turbulence). According to the actual atmospheric conditions at the time of imaging, a certain typical value is selected as the atmospheric turbulence structure constant The initial value of , and the equivalent lens focal length and propagation distance of the compressed sensing broadband hyperspectral imaging system based on random gratings are brought into formula (1) to obtain the optical transfer function H(u of atmospheric turbulence under different imaging bands; λ i ); Fourier transform is performed on the optical transfer function formula (1) under each imaging band, and the results are arranged in the diagonal direction of the matrix, which is the atmospheric turbulence transfer matrix under long exposure time
其中l是基于随机光栅的压缩感知宽波段高光谱成像系统的谱段数。将预制的基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵AGISC与生成的大气湍流传输矩阵相乘，获取总体测量矩阵where l is the number of spectral bands of the stochastic grating based compressive sensing broadband hyperspectral imaging system. Combine the prefabricated random grating-based compressed sensing broadband hyperspectral imaging system measurement matrix A GISC with the generated atmospheric turbulence transfer matrix Multiply to get the overall measurement matrix
利用线性或非线性的压缩感知算法，求解如下Using linear or nonlinear compressive sensing algorithm, the solution is as follows
问题，将获取的基于随机光栅的压缩感知宽波段高光谱成像系统接收受到大气湍流影响的采样数据Y重构为多光谱图像结果 The problem is to reconstruct the obtained sampling data Y affected by atmospheric turbulence by the random grating-based compressive sensing broadband hyperspectral imaging system into a multispectral image result
已知不受大气湍流影响的多光谱图像满足相似性和低峭度特性，判断重构图像结果是否满足多光谱图像的相似性和低峭度特性，如果满足，则利用多波长图像合成技术，将重构的多光谱图像结果合成为全色图像，实现消除大气湍流影响；否则修正大气湍流的大气湍流结构常数，带入大气湍流的光学传递函数中，再对修正后光学传递函数进行Fourier变换，如公式(2)所示按照矩阵对角方向排列生成修正的大气湍流传输矩阵根据公式(3)，预制的基于随机光栅的压缩感知宽波段高光谱成像系统的测量矩阵AGISC与此修正的大气湍流传输矩阵相乘，获取新的总体测量矩阵，再求解公式(4)，判断重构多光谱图像是否满足多光谱图像的相似性和低峭度特性。重复上述过程，直至重构多光谱结果满足多光谱图像的相似性和低峭度特性，再利用多波长图像合成技术，将重构的多光谱图像结果合成为全色图像，获取消除大气湍流影响的图像，从而实现消除大气湍流影响。It is known that the multispectral image that is not affected by atmospheric turbulence satisfies similarity and low kurtosis characteristics, and judges the result of the reconstructed image Whether it satisfies the similarity and low kurtosis characteristics of multispectral images, and if so, use multiwavelength image synthesis technology to synthesize the reconstructed multispectral image results into a panchromatic image to eliminate the influence of atmospheric turbulence; otherwise correct the effect of atmospheric turbulence Atmospheric turbulence structure constants are brought into the optical transfer function of atmospheric turbulence, and then Fourier transform is performed on the corrected optical transfer function. As shown in formula (2), the modified atmospheric turbulence transfer matrix is generated according to the diagonal direction of the matrix According to formula (3), the measurement matrix A GISC of the prefabricated stochastic grating-based compressive sensing broadband hyperspectral imaging system and this modified atmospheric turbulence transfer matrix Multiply to obtain a new overall measurement matrix, and then solve the formula (4) to judge whether the reconstructed multispectral image satisfies the similarity and low kurtosis characteristics of the multispectral image. Repeat the above process until the reconstructed multispectral results meet the similarity and low kurtosis characteristics of multispectral images, and then use multi-wavelength image synthesis technology to synthesize the reconstructed multispectral images into panchromatic images to obtain and eliminate the influence of atmospheric turbulence image, so as to eliminate the influence of atmospheric turbulence.
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