Image enlargement with high-frequency component augmentation based on predefined codebook describing edge blurring properties

Image super-resolution as high-quality image enlargement is achieved by some type of restoration for high-frequency components that deteriorate through the image enlargement. The estimation methods using the given image itself are effective for the restoration, and we have proposed a method employing the codebook describing edge blurring properties that are derived from the given image. It is, however, unfavourable to apply those image-dependent methods to movies whose scene varies momentarily. In this paper, an image-independent codebook incorporating local edge patterns of images is proposed, and then the predefined codebook is applied. The effectiveness is shown through some experiments.     

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.     

An improved optical identity authentication system with significant output images

An improved method for optical identity authentication system with significant output images is proposed. In this method, a predefined image is digitally encoded into two phase-masks relating to a fixed phase-mask, and this fixed phase-mask acts as a lock to the system. When the two phase-masks, serving as the key, are presented to the system, the predefined image is generated at the output. In addition to simple verification, our method is capable of identifying the type of input phase-mask, and the duties of identity verification and recognition are separated and, respectively, assigned to the amplitude and phase of the output image. Numerical simulation results show that our proposed method is feasible and the output image with better image quality can be obtained.     

一种新的空间域图像错误掩盖方法

提出了空间域图像错误掩盖方法.在信道丢包率较高时,采用场编码交织技术将图像按像素行分为两个场,并分别独立编码和传输.当某个场中的图像数据在网络传输过程中丢失时,用相邻场的像素值通过插值的方法恢复丢失数据.实验结果表明,掩盖效果明显优于现有的空间域错误掩盖方法,即使在图像数据丢失一半的情况下,恢复图像主观上仍可接受,测试图像的PSNR增益可达2.77~7.24 dB.     

Pulse Coupled Neural Network-Based Multimodal Medical Image Fusion via Guided Filtering and WSEML in NSCT Domain

Multimodal medical image fusion aims to fuse images with complementary multisource information. In this paper, we propose a novel multimodal medical image fusion method using pulse coupled neural network (PCNN) and a weighted sum of eight-neighborhood-based modified Laplacian (WSEML) integrating guided image filtering (GIF) in non-subsampled contourlet transform (NSCT) domain. Firstly, the source images are decomposed by NSCT, several low- and high-frequency sub-bands are generated. Secondly, the PCNN-based fusion rule is used to process the low-frequency components, and the GIF-WSEML fusion model is used to process the high-frequency components. Finally, the fused image is obtained by integrating the fused low- and high-frequency sub-bands. The experimental results demonstrate that the proposed method can achieve better performance in terms of multimodal medical image fusion. The proposed algorithm also has obvious advantages in objective evaluation indexes VIFF, Q_W, API, SD, EN and time consumption.     

顾及光谱混叠的高光谱相机任意方向侧扫几何成像

以移动平台的线推扫式高光谱相机横向推扫成像不同于以卫星平台或飞机平台的竖直摄影成像方式,其属于水平方向推扫竖直方向成像,存在投影面选择、空间方位确定以及光顾混叠等问题。针对上述情况,详细推导了适合于线阵高光谱相机地面推扫的影像像素地理参考模型,可以进行任意方向的地面横向推扫成像;结合影像的地面采样间隔大小及推扫成像的区域范围,给出了地理参考后影像格网划分的一般过程;同时,考虑到在影像格网划分过程中存在的舍入误差,以及在影像校正过程中采用传统直接光谱采样可能造成的光谱掺杂问题,提出了基于地理参考后相邻像素重叠面积作为权重系数进行加权融合的改进光谱采样方法。最后进行了大量地面横向推扫成像实验,并依据上述算法进行了影像畸变校正,验证了线阵影像几何畸变校正算法的有效性及鲁棒性,同时,对校正好后的影像选用多个样本点进行了光谱数据验证,实验表明改进后的光谱采样方法明显优于直接光谱采样算法,为同类产品的地面应用提供参考。     

卷积稀疏表示图像融合与超分辨率联合实现

为避免图像融合与超分辨率分步实现的不足,提出了基于卷积稀疏表示的融合与超分辨率重建联合实现方法。假设低分辨率与高分辨率图像之间具有相同的稀疏特征图,设计了一种高、低分辨率滤波器联合学习框架,实现对图像高低频成分的分离,并根据不同成分的形态特性设计了不同的融合规则:对于高频成分,根据稀疏特征图亮度信息和像素活跃性水平,设计了一种像素显著性度量方案来指导高频特征图的融合;对于低频成分,根据脉冲耦合神经网络能捕获邻域相似像素点火的特性,设计了低频成分融合方法。所提方法不需要将图像分割成重叠的块,避免块向量化的缺陷。实验结果表明,能有效提高图像融合的质量。     

光学显微镜自动聚焦取窗方法研究

针对全自动光学显微镜系统中,传统聚焦窗口选择方法易受图像内容分布、杂质、噪声等因素干扰的问题,提出一种根据内容像素变化量选择聚焦窗口的方法。该方法将灰度差像素数量与边缘像素数量加权作为内容像素数量,据此衡量失焦模糊状态下子块内容含量并划分聚焦窗口,减少杂质与噪声对取窗过程的影响;用降采样后图像各子块内容含量估计原图像内容分布信息,降低图像滤波、梯度计算过程的计算量;使用局部标准差与锐利边缘像素数量联合检测焦平面图像的失焦模糊区域,有效排除玻片杂质造成的焦平面误判。与传统的显微镜自动聚焦取窗方法相比,对内容丰富程度和分布状况不同的显微图像序列,该方法均能获取有效的聚焦窗口,像素梯度均值更高,所得的评价曲线局部极值极少,尖锐性好,因此该方法的成功率高,鲁棒性更强。     

Multifocus image fusion scheme using focused region detection and multiresolution

To solve the fusion problem of the multifocus images of the same scene, a novel algorithm based on focused region detection and multiresolution is proposed. In order to integrate the advantages of spatial domain-based fusion methods and transformed domain-based fusion methods, we use a technique of focused region detection and a new fusion method of multiscale transform (MST) to guide pixel combination. Firstly, the initial fused image is acquired with a novel multiresolution image fusion method. The pixels of the original images, which are similar to the corresponding initial fused image pixels, are considered to be located in the sharply focused regions. By this method, the initial focused regions can be determined, and the techniques of morphological opening and closing are employed for post-processing. Then the pixels within the focused regions in each source image are selected as the pixels of the fused image; meanwhile, the initial fused image pixels which are located at the focused border regions are retained as the pixels of the final fused image. The fused image is then obtained. The experimental results show that the proposed fusion approach is effective and performs better in fusing multi-focus images than some current methods.     

A novel image encryption method based on total shuffling scheme

In this paper, a novel image encryption method based on skew tent chaotic map and permutation-diffusion architecture is proposed. In the proposed method, the P-box is chosen as the same size of plain-image, which shuffles the positions of pixels totally. The keystream generated by skew tent chaotic map is related to the plain-image. Statistical analysis, information entropy analysis, and sensitivity analysis to plaintext and key on the proposed scheme are provided in this paper. It can be seen that this algorithm is efficient and reliable, with high potential to be adopted for network security and secure communications.     

一种基因芯片光学扫描图像倾斜校正方法研究

针对在基因芯片光学扫描时产生的图像倾斜问题,提出了一种基于像素灰度的芯片图像倾斜校正方法。结合基因芯片图像的结构特点,基于行、列方向像素灰度定义芯片图像的校正指标。在角度检测范围内,利用折半搜索方法,基于校正指标来检测芯片图像的校正角度和芯片图像的校正位置。实验结果表明,该方法能有效地检测多类基因芯片图像的倾斜角度,具有较强的鲁棒性和实用性。     

基于偏最小二乘算法的人脸图像超分辨率技术

提出了基于偏最小二乘法回归的超分辨率复原算法.介绍了偏最小二乘法回归算法的原理,研究和分析了基于偏最小二乘法回归的超分辨率复原算法.将高低分辨率图像块的高频信息和中频信息作为其特征,并采用分块重叠的方法解决了复原时存在的方块效应.通过对亚洲人脸和欧美人脸的实验结果表明,提出的方法无论是对亚洲人脸还是欧美人脸都能取得较好的复原效果,并且在放大倍数较大的情况下,复原的效果仍然显著.     

A New Quantum Gray-Scale Image Encoding Scheme

In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the original one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images.     

Small target detection using bilateral filter and temporal cross product in infrared images

We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.     

基于信息理论的γ能谱辨识新方法

提出了一种基于相对熵的放射源γ能谱识别方法。首先,利用主成分分析(PCA)算法压缩数据,构造γ射线能谱的特征空间。然后,采用随机化技术(RT)来使特征空间中γ射线能谱的特征值归一化,这样,γ射线能谱的特征空间可以看作是概率空间。最后,定义两个概率空间的相对熵来测量两个γ射线能谱的相对差异。大量实验表明,所提方法能够更加有效地辨识γ射线能谱, 不仅计算量小,而且对诸如统计浮动、谱峰偏移、底噪等因素具有很高的鲁棒性。     

Adaptive threshold selection for background removal in fringe projection profilometry

In fringe projection profilometry, background and shadow are inevitable in the image of an object, and must be identified and removed. In existing methods, it is nontrivial to determine a proper threshold to segment the background and shadow regions, especially when the gray-level histogram of the image is close to unimodal, and an improper threshold generally results in misclassification of the object and the background/shadow. In this paper, an adaptive threshold method is proposed to tackle the problem. Different from the existing automatic methods, the modulation-level histogram, instead of the gray-level histogram, of the image is employed to determine the threshold. Furthermore, a new weighting factor is proposed to improve Otsu's method to segment the image with a histogram close to unimodal, and the modulation difference of the object pixels and the background/shadow pixels is intensified significantly by the weighting factor. Moreover, the weighting factor is adaptive to the image. The proposed method outperforms existing methods either in accuracy, efficiency or automation. Experimental results are given to demonstrate the feasibility and effectiveness of the proposed method.     

Digital information encrypted in an image using binary encoding

This paper proposes a new type of encoding methods to encrypt hidden (covert) information in host images. The encrypted information can be plot, fax, word, or network data, and it must be encoded with binary codes. All the pixels in an encoded (overt) image modulated from a host image are classified into three groups. The first group of pixels is called identification codes, used to judge whether the overt image is encoded by a method proposed in this paper or not. The second group of pixels is called type codes, used to judge the encoding type. The third group of pixels is called information codes, used to decode the encoded information. Applying the proposed encoding methods is quite convenient, and host images are not needed for decoding. Decoding covert information from overt images is rather difficult for un-authorized persons, whereas it is very easy for designers or authorized persons. Therefore, the proposed methods are very useful.     

Two image denoising approaches based on wavelet neural network and particle swarm optimization

Two image denoising approaches based on wavelet neural network (WNN) optimized by particle swarm optimization (PSO) are proposed. The noisy image is filtered by the modified median filtering (MMF).Feature values are extracted based on the MMF and then normalized in order to avoid data scattering. In approach 1, WNN is used to tell those uncorrupted but filtered by MMF and then the pixels are restored to their original values while other pixels will retain. In approach 2, WNN distinguishes the corrupted pixels and then these pixels are replaced by MMF results while other pixels retain. WNN can be seen as a classifier to distinguish the corrupted or uncorrupted pixels from others in both approaches. PSO is adopted to optimize and train the WNN for its low requirements and easy employment. Experiments have shown that in terms of peak signal-to-noise ratio (PSNR) and subjective image quality, both proposed approaches are superior to traditional median filtering.     

一种基于中性集和均值漂移的彩色遥感图像非监督建筑物提取方法

建筑物的纹理和光谱信息的多样性一直是自动化识别的瓶颈。针对此问题,提出了一种彩色遥感图像建筑物提取方法,该算法结合中性集和均值漂移,对转换到中性集空间的影像进行均值漂移分割,生成以影像中主要地物类型为核心的光谱类别图像,提取建筑物。通过中性集空间的增强及分割,克服了传统均值漂移分割稳定性低、光谱不连续及信息混杂的缺陷,避免了地物识别前提取连通区等操作。实验证明,提出的算法可以简捷、完整、准确、稳定地提取建筑物,满足高分辨率遥感影像建筑物的提取要求。     

基于双字典和稀疏表示的医学图像超分辨率重建

在医学影像图像处理过程中,由于成像技术和成像时间的限制,还无法获取满足诊断需求的清晰图像,这使得在现有技术和极短时间内所获取的医学病理图像需要进行超分辨率的重建处理;基于学习的图像超分辨率思想是从已建立的先验模型中重建出高频细节;在文章中,将要估计的高频信息认为是由主要高频和冗余高频两部分组成,提出了一种基于双字典学习和稀疏表示的医学图像超分辨率重建算法,由主要字典学习和冗余字典学习组成,分别渐近地恢复出主要高频细节和冗余高频细节;实验结果的数据分析和视觉效果显示,所提出双层递进方法能够恢复更多的图像细节且在性能指标上比现有的其他几种方法均有所提高。