Image super-resolution based on local self-similarity

A new image super-resolution method based on a codebook mapping is proposed. The codebook mapping represents the internal relationship between low-and high-frequency image components, and is used for the estimation of highfrequency image components lost in the sampling process. In the proposed method, codebooks are first generated by the low-and high-frequency image components of the original image itself that is to be processed. Then, a resultant superresolution image, that is, an enlarged image, is obtained by combining the estimated high-frequency image components with the low-frequency ones obtained by a typical interpolation-based method. The effectiveness of the proposed method is verified by comparing it against some conventional methods.     

基于小波包和Niblack法的枪号图像二值化算法

针对枪号图像字符易磨损、对比度太大或太小的特点,提出了小波包滤波器浮动阈值和Niblack法相结合的二值化算法.首先采用小波包滤波器对图像滤波,把得到的低通图像作为浮动阈值,并对图像进行二值化,得到第一幅待融合图像;然后采用Niblack法对图像进行二值化,得到第二幅待融合图像;最后把两幅图像按照灰度最小的方法进行融合,得到最终的二值化图像.实验结果表明该综合算法在二值化效果、适用范围等方面均有良好的表现,具有一定的推广价值.     

Fast image enlargement using predefined codebook and eigenspace backprojection for lost pixel

In this paper, a new image enlargement method applying the backprojection for lost pixel (BPLP) to the predefined codebook-based method is proposed. BPLP is a method for image restoration. In BPLP, the eigenspace reflecting the characteristics of an input image is generated from the remained pixels and is used to restore the missing pixels. In the proposed method, the eigenspace is replaced by one generated from the predefined codebook (PDC). PDC represents edge-blurring properties in a small image patch and consists of pairs of low- and high-frequency image patches on various edge patterns. By replacing the PDC-based estimation of lost high-frequency components with BPLP, a fast image enlargement method retaining its performance can be developed. Through some experiments, the effectiveness of the proposed method was demonstrated. Especially, it was confirmed that the processing time of the proposed method was shortened to about 1/50 that of the PDC-based method.     

ARM架构下计算机图像并行化处理技术研究

为在图像处理与分析时具备良好的视觉效果,提高图像处理的速度,需要对ARM架构下计算机图像并行化处理技术进行研究。当前采用的方法是对各种变换频域图像特征提取与计算机图像集合特征的提取进行相结合,克服了当前对图像进行提取时存在图像形状描述的缺陷,提取图像特征向量维数相对较低。实验表明,通过对图像进行特征提取能很好的对图像效果进行展示,将图像的纹理特征进行详细的表述,将该方法应用到图像处理技术当中,具有良好的去噪效果及扩展性,该方法过程简单,但存在图像视觉效果较差的问题。为此,提出一种ARM架构下计算机图像并行化处理技术研究方法。该方法首先利用非局部均值去噪算法对图像进行去噪处理,然后结合图像去噪的结果利用小波变换对去噪图像进行边缘检测,最后采用非线性增强算法对图像进行增强完成对ARM架构下计算机图像并行化处理技术研究。实验结果表明,所提方法不仅提高图像处理速度,还提高图像视觉效果,具有广泛的应用价值。     

像素随机映射的快速算法及在LSB隐藏技术中的应用

提出一种像素随机映射的快速方法, 将该方法与像素字节低位隐藏信息的LSB(Least Significant Bit)技术相结合, 讨论了将RGB彩色图像作为载体隐匿真彩色图像、灰度图像、二值图像及全息信息的方法. 研究结果表明, 该方法加密及解密效率高, 载体图像具有较好的抗破译及抗剪切能力. 根据隐藏信息的性质合理使用LSB技术, 能在基本不影响载体图像质量的情况下较好地隐匿多种信息.     

Single image deblurring using novel image prior constraints

Single image deblurring is a highly ill-posed problem and requires to be regularized. Many common forms of image prior have a major drawback that is unable to make full use of local image information. In this paper, we propose a single image deblurring method using novel image prior constraints. We establish a probabilistic model by enforcing inspired image prior constraints and adopt an advanced iterative scheme that alternates between blur kernel estimation and non-blind image restoration. To suppress ringing artifacts caused by inevitable blur kernel estimated errors, our method employs total variation image restoration and presents an alternation half-quadratic algorithm to solve the non-convex cost function. Finally, experiments show that our method has good performance in suppressing ringing artifacts, and makes a good balance between alleviating staircase effects and preserving image details.     

一种保持非负整数值的图像加密算法

提出了一种能够使双随机相位图像加密方法的密文图像保持为非负整数值的变换——重构变换.重构变换包括预处理和频谱搬移两个过程,其主要特点为,在图像进行频域变换之前,通过叠加的方式将整数图像压缩成一半大小的复数图像,从而能缩小后续运算的计算空间;基于重构变换的双随机相位图像加密方法可以实现联合图像压缩和加密的效果.与基于混沌系统的数字图像加密方法相比,本文方法的密文图像具有更低的信息熵.实验结果表明,该方法具有较强的安全性,解密图像基本无失真,并且密文图像对加性噪音攻击具有一定的鲁棒性.     

A novel cellular automata based technique for visual multimedia content encryption

This paper proposes a new method for visual multimedia content encryption using Cellular Automata (CA). The encryption scheme is based on the application of an attribute of the CLF XOR filter, according to which the original content of a cellular neighborhood can be reconstructed following a predetermined number of repeated applications of the filter.The encryption is achieved using a key image of the same dimensions as the image being encrypted. This technique is accompanied by the one-time pad (OTP) encryption method, rendering the proposed method reasonably powerful, given the very large number of resultant potential security keys. The method presented here makes encryption possible in cases where there is more than one image with the use of just one key image. A further significant characteristic of the proposed method is that it demonstrates how techniques from the field of image retrieval can be used in the field of image encryption. The proposed method is further strengthened by the fact that the resulting encrypted image for a given key image is different each time. The encryption result depends on the structure of an artificial image produced by the superposition of four 1-D CA time-space diagrams as well as from a CA random number generator.A semi-blind source separation algorithm is used to decrypt the encrypted image. The result of the decryption is a lossless representation of the encrypted image. Simulation results demonstrate the effectiveness of the proposed encryption method. The proposed method is implemented in C# and is available online through the img(Rummager) application.     

一种保持非负整数值的图像加密算法

提出了一种能够使双随机相位图像加密方法的密文图像保持为非负整数值的变换——重构变换.重构变换包括预处理和频谱搬移两个过程,其主要特点为,在图像进行频域变换之前,通过叠加的方式将整数图像压缩成一半大小的复数图像,从而能缩小后续运算的计算空间;基于重构变换的双随机相位图像加密方法可以实现联合图像压缩和加密的效果.与基于混沌系统的数字图像加密方法相比,本文方法的密文图像具有更低的信息熵.实验结果表明,该方法具有较强的安全性,解密图像基本无失真,并且密文图像对加性噪音攻击具有一定的鲁棒性.     

Three-dimensional image correlator using fast computational integral imaging reconstruction method based on pixel-to-pixel mapping

In this paper, a three-dimensional (3D) image correlator using a fast computational integral imaging reconstruction (CIIR) method based on a pixel-to-pixel mapping is proposed. In order to implement the fast CIIR method, we replace the magnification process in the conventional CIIR by a pixel-to-pixel mapping. The proposed fast CIIR method reconstructs two sorts of plane images; a plane image whose quality is sufficient, and a dot pattern plane image insufficient to view. This property is very useful to enhance the performance of a CIIR-based image correlator. Thus, we apply the fast CIIR method to a CIIR-based image correlator. To show the feasibility of the proposed method, some preliminary experiments on both pattern correlation and computational cost are carried out, and the results are presented. Our experimental results indicate that the proposed image correlator is superior to the previous method in terms of both correlation performance and complexity.     

Hybrid encoding method by assembling the magic-matrix scrambling method and the binary encoding method in image hiding

The magic-matrix scrambling method and the binary encoding method are combined to form a hybrid encoding method for hiding digital covert images. For this hybrid encoding method, a covert image is encoded into a host image to form an overt image. First, the magic-matrix scrambling method is used to rearrange all the pixels of the covert image by using a specified magic matrix modified from a magic square to form a scrambled matrix. Then, all the pixels of the scrambled matrix are denoted by binary data. Finally, the binary data are encoded into the host image to form the overt image. The pixels of the overt image contain nine groups of codes used for decoding the covert image, i.e. identification codes, covert-image dimension codes, scrambling-time codes, magic-square dimension codes, corner codes, shifting codes, arrangement codes, graylevel codes, and information codes. The overt image and the host image look almost the same for eyes. Furthermore, the covert image can be decoded directly from the overt image without using the host image. The most important feature is that the decoded covert image is identical to the original covert image, i.e. there is no distortion in the decoding work.     

超微弱光子图像的相关检测及计算机模拟

在超微弱发光的研究中（例如生物发光）,由于发光强度极弱,由像增强器得到的光子图像由于样本（光子）数量太少和受系统暗噪声的影响使其信噪比极低,提出了一种基于统计学的光子图像相关积分方法和基于相关处理的光子图像处理方法,用累积光子来提高图像信噪比并得到相应灰度图像并对该方法进行了计算机模拟,同时展示了光子图像和传统灰度图像的信噪比关系,是进行微弱生物发光信号检测的有效方法。     

Encrypting image by assembling the fractal-image addition method and the binary encoding method

The fractal-image addition method and the binary encoding method are assembled to form a hybrid method for encrypting a digital covert image. For this hybrid method, a host image is used to create an overt image with the information of the covert image. First, the fractal-image addition method is used to add some fractal images and the covert image to form an image-mixing matrix. Then, all the pixel values of the image-mixing matrix are transferred into binary data. Finally, the binary data are encoded into the host image to create an overt image. The pixels of the overt image contain eight groups of codes used for reconstructing the covert image. The eight groups of codes are identification codes, row amount codes, covert-image dimension codes, fractal-image amount codes, starting-pixel codes, character amount codes, character codes, and information codes. The overt image and the host image look almost the same for eyes. Furthermore, the covert image can be directly reconstructed from the overt image without using the host image. The most important feature is that the reconstructed covert image is identical to the original covert image, i.e. there is no distortion in the decoding work.     

Image fusion using non-separable wavelet frame

In this paper, an image fusion method is proposed based on the non-separable wavelet frame (NWF) for merging a high-resolution panchromatic image and a low-resolution multispectral image. The low-frequency part of the panchromatic image is directly substituted by multispectral image. As a result, the multispectral information of the multispectral image can be preserved effectively in the fused image. Due to multiscale method for enhancing the high-frequency parts of the panchromatic image, spatial information of the fused image can be improved. Experimental results indicate that the proposed method outperforms the intensity-hue-saturation (IHS) transform, discrete wavelet transform and separable wavelet frame in preserving spectral and spatial information.     

基于单站地基望远镜的空间目标姿态估计方法

为实现从单站光测图像中估计出已知3D模型的空间目标姿态,利用Vega Prime提出了一种采用仿真图像进行相关度局部最优搜索的姿态估计方法,该方法无需建立2D-3D特征投影关系和大量的模型匹配库。首先,对输入图像进行图像预处理,获得目标原始图像。然后,利用Vega Prime加载目标3D模型生成仿真匹配图像,并进行图像预处理获得目标匹配图像,计算两幅图像相关度。最后,更新3D目标模型姿态,直至仿真匹配图像与目标原始图像的相关度值取得局部最优,输出目标模型姿态。仿真实验结果表明,采用本文所提方法的观测仿真图像姿态平均估计误差为3.85°,仿真原图可实现姿态准确估计,表明该方法是一种空间目标姿态估计的有效方法。     

一种新的基于关键子块的图像检索算法

为了将有效的文本检索技术应用到图像检索中,结合人眼视觉特性及方块编码的思想,提出了一种基于图像关键子块的检索算法.即首先利用图像方块编码的思想将图像预先分成互不重叠的子图像块,然后利用方块编码的思想,根据块的灰度差对这些子图像进行独立地编码,这些子图像的方块编码构成的块不仅能有效的描述图像的纹理内容,而且可以反映图像的形状分布和边缘分布.以此来定义图像的关键子块.最后借助文本检索技术来实现图像检索.同时,考虑到不同类型关键子块在图像中出现的频度对检索效果的影响,又提出了相应的改进算法.实验结果表明,该算法是有效的.     

基于场景的红外焦平面阵列非均匀性评价方法

针对红外遥感图像非均匀性的定量评价问题,研究了基于场景的红外焦平面阵列响应非均匀性的定量评价方法。利用真实红外遥感图像序列量值分布的特点,针对小序列图像提出了基于序列排序和小波变换的标准图像构建算法;结合非均匀性评价指标,提出了利用构建标准图像的响应非均匀性对红外图像的非均匀性进行定量估计;分别利用黑体定标实验和统计方法对标准图像构建算法进行了验证,同时进行了不同校正算法的剩余非均匀性评价实验。结果表明,128frame序列构建得到的标准图像的非均匀性分别比同温黑体图像小0.92%,比统计标准图像大0.59%。该方法可用于定量估计红外遥感图像的非均匀性。     

相位一致性图像及其在目标跟踪中的应用(英文)

针对传统实时相关跟踪方法对照度变化敏感的问题,提出了一种基于相位一致性图像的相关跟踪方法.利用相位一致性函数值在[0,1]区间内且无量纲、对图像的亮度和对比度具有不变性等特点,首先对原始图像进行相位一致性检测,得到相位一致性图像,再利用MAD(Minimum Absolute Difference)等相关跟踪算法在相位一致性图像中对目标进行跟踪运算.对可见光和红外图像的实验表明,在图像的亮度和对比度发生剧烈变化的情况下,算法仍能保持对目标的稳定跟踪.该方法可用于解决传统实时相关跟踪方法普遍存在的因照度变化导致跟踪点漂移甚至跟踪失败的问题.     

基于AM测度及混合优化算法的图像配准方法

介绍了一种基于边缘特征的图像配准方法。首先利用Canny算子提取图像的边缘;然后以AM测度作为配准准则,在优化AM峰值和配准参数的时候,先用遗传算法将配准参数收敛到最优值附近,再使用Powell法进行局部搜索;最后对待配准图像进行刚体变换及双线性插值,从而实现图像配准。实验结果表明,此优化方法不仅提高了计算速度,而且提高了配准精度,配准结果达到了亚像素级水平。     

An image reconstruction method based on the double-random phase encoding system in the Fresnel domain

A method used to reconstruct the image from the frequency spectrum intensity of an encrypted image is proposed in this paper. The encrypted image is obtained by utilizing the double-random phase encoding technology in the Fresnel domain on a symmetrical original image. The frequency spectrum intensity of an encrypted image is received by a CCD, and transformed to a computer. With the help of an algorithm, involving autocorrelation and complex-convolution in the discrete Fresnel transform, a reconstructed image that is the same as the original image could be obtained. Numerical simulation shows that our method is only effective for a symmetrical original image. Discussion on the influence of the deviation of pixel value in the position of symmetry has also been provided in this paper.