闪光照相系统成像重复性的测量

为了更直观利用照像图像信息考察照相系统的重复性,提出了利用等光程条件下的黑密度分布曲线对成像重复性进行测量的方法,通过两次成像的黑密度分布曲线的线性拟合参数来评估成像系统的成像重复性。实验测量了有无后锥条件下的闪光照相系统的重复性以及底片接收系统的成像重复性,实验结果表明:后锥的存在对成像重复性没有明显影响,底片接收时闪光照相系统的成像重复性约为5％,底片本身引入的成像重复误差约为1.6％。     

“天光一号”平滑化角多路系统的建立

采用诱导空间非相干（FEISI）的平滑方法结合传递傅里叶面的技术,建立了一套平滑化六束角多路系统。该系统输出总能量158 J,能量稳定度约4％,输出脉冲宽度25 ns,靶面有效焦斑直径400 μm,焦斑均匀性1.6％,激光功率密度3.7×1012 W/cm2。     

An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map

Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.     

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption. The parallel compressed sensing method is adopted to ensure the encryption and decryption efficiency. The ZUC stream cipher is used to sample the one-dimensional chaotic map to reduce the correlation between elements and improve the randomness of the chaotic sequence. The compressed sensing measurement matrix is constructed by using the sampled chaotic sequence to improve the image restoration effect. In order to reduce the block effect after the parallel compressed sensing operation, we also propose a method of a random block of images. Simulation analysis shows that the algorithm demonstrated better encryption and compression performance.     

Lossless Medical Image Compression by Using Difference Transform

This paper introduces a new method of compressing digital images by using the Difference Transform applied in medical imaging. The Difference Transform algorithm performs the decorrelation process of image data, and in this way improves the encoding process, achieving a file with a smaller size than the original. The proposed method proves to be competitive and in many cases better than the standards used for medical images such as TIFF or PNG. In addition, the Difference Transform can replace other transforms like Cosine or Wavelet.     

Deep Image Steganography Using Transformer and Recursive Permutation

Image steganography, which usually hides a small image (hidden image or secret image) in a large image (carrier) so that the crackers cannot feel the existence of the hidden image in the carrier, has become a hot topic in the community of image security. Recent deep-learning techniques have promoted image steganography to a new stage. To improve the performance of steganography, this paper proposes a novel scheme that uses the Transformer for feature extraction in steganography. In addition, an image encryption algorithm using recursive permutation is proposed to further enhance the security of secret images. We conduct extensive experiments to demonstrate the effectiveness of the proposed scheme. We reveal that the Transformer is superior to the compared state-of-the-art deep-learning models in feature extraction for steganography. In addition, the proposed image encryption algorithm has good attributes for image security, which further enhances the performance of the proposed scheme of steganography.     

部分相干光学系统最佳象面的性质讨论

在部分相干理论的基础上,分别用表观传递函数和能量分布作评价指标,计算了部分相干光学系统的最佳象面位置,并讨论了其与相干度、空间频率及象差的关系。     

Generalization of Strang's Preconditioner with Applications to Toeplitz Least Squares Problems

In this paper, we propose a method to generalize Strang's circulant preconditioner for arbitrary n-by-n matrices A_n. The th column of our circulant preconditioner Sn is equal to the th column of the given matrix A_n. Thus if A_n is a square Toeplitz matrix, then Sn is just the Strang circulant preconditioner. When Sn is not Hermitian, our circulant preconditioner can be defined as . This construction is similar to the forward-backward projection method used in constructing preconditioners for tomographic inversion problems in medical imaging. We show that if the matrix A_n has decaying coefficients away from the main diagonal, then is a good preconditioner for An. Comparisons of our preconditioner with other circulant-based preconditioners are carried out for some 1-D Toeplitz least squares problems: min ∥ b - Ax∥₂. Preliminary numerical results show that our preconditioner performs quite well, in comparison to other circulant preconditioners. Promising test results are also reported for a 2-D deconvolution problem arising in ground-based atmospheric imaging.     

基于聚类分割和形态学的可见光与SAR图像配准

针对可见光与SAR图像灰度差异大,共有特征提取难的问题,提出了一种基于k-均值聚类分割和形态学处理的轮廓特征配准方法。利用k-均值聚类算法对两类图像进行分割,得到图像分割区域;通过形态学处理,有效减少SAR图像斑点噪声影响,准确提取两类图像的封闭轮廓;采用轮廓不变矩理论,引入矩变量距离均值、方差约束机制和一致性检查的匹配策略,获取最佳匹配对,实现了两类图像的配准。通过实验,三组图像的配准精度分别达到0.3450、0.2163和0.1810,结果表明该法可行且能达到亚像素的配准精度。     

基于能量分布的红外像点定位分析方法

在红外探测器的应用中,常用统计分析、算例验证等方法研究目标成像精确定位问题。鉴于上述方法难以充分阐释物理意义与揭示普遍规律,提出基于能量分布及成像特征的分析方法,针对红外探测目标成像精确定位问题,利用能量分布和数字图像中成像规律,研究像点定位及精度分析。研究了红外目标成像和数字图像特点,建立了定位模型和方法流程;分析了定位误差影响因素,实现了定位结果精度评定;最后结合典型应用实例,进行了计算验证。该方法与已有方法相比,分析过程更直观,获取了红外像点定位分析的理论依据,并给出了定位结果的精度水平:通常红外成像应用中,精度优于1/6像元;在成像较大时,精度可达1/10像元以上。该研究结论对红外探测应用中目标准确定位具有重要意义。