基于两帧图像"亚像元"技术的插值方法研究

分析了两帧图像“亚像元”法的图像数据特征、插值处理的可行性以及提高图像空间分辨率的合理性。推导出三种插值方法——双线性插值、加权插值和线性代数插值的计算公式。在Matlab下进行模拟“亚像元”技术的插值计算,计算结果表明图像分辨率确能提高到“半个探测器像元”的空间分辨率。并对三种插值方法进行了比较。     

亚像元图像超分辨率重建研究

针对光纤束耦合成像系统的特点,对存在亚像元量级空间错位的图像进行超分辨率重建研究。研究分为图像配准与融合两个步骤。图像配准时,用经典的Keren配准算法对两幅图像进行亚像元级别配准。图像融合时结合双三次插值对配准后两幅图像进行Mallat小波分解与重构,从而实现图像超分辨率重建。实验结果表明,简化后的配准算法配准精度达到了0.01像素,而经过插值与融合重建出来的图像空间分辨率提高了一倍,并且保留了丰富的细节信息。     

红外凝视成像光学微扫描重建技术研究

由于有限的焦平面阵列等因素影响,红外热成像系统的空间分辨率较低.理论上,微扫描能有效提高空间分辨率,然而光学系统不易精确控制,导致重建图像模糊.针对此问题,本文提出了基于帧间块匹配的图像配准算法.该算法有效地实现了亚像元成像,在提高空间分辨率的同时,抑制了图像模糊.     

亚像元技术在图像采集系统中的应用

指出利用亚像元技术来提高图像采集系统空间分辨率,不仅要在理论上研究亚像元技术的性能以及图像超分辨率重建算法,还要研究亚像元技术受到系统其他因素的影响以及亚像元技术对系统其他性能的影响.分析了图像配准程度、光学系统点扩散函数以及仪器信噪比和亚像元技术的相互影响关系,并得到结论根据系统不同工作环境进行设计以保证亚像元技术带来的空间分辨率的提高和系统其他性能的平衡,是在系统中正确运用亚像元技术的关键.     

一种亚像素级图像超分辨恢复算法

随着光学成像到光电数字成像的转变,如何提高CCD的几何分辨率,已成为研制高分辨光电成像系统亟待解决的问题.建立了半像元超分辨成像数学模型,提出了半像元的CCD几何超分辨方法.该方法将2片线阵CCD集成在同一器件中,在线阵方向上错开半个像元,同时读出时间减半,最终交织重组图像数据,以合成高分辨率图像.利用MATLAB软件对双线性插值方法及半像元成像方法进行了仿真,并定性定量地分析了2种方法的效果.结果显示：半像元方法合成图像分辨率约为低分辨率图像的2倍,且2组仿真图像中的PSNR比双线性插值图像分别高出1.486 4 dB和2.207 0 dB.该方法可以显著地减轻欠采样引起的图像模糊,且实时性优于双线性插值方法.     

一种新型基于利用全色锐化技术的插值高光谱图像亚像元定位

利用全色锐化技术提出了一种新型基于插值的高光谱图像亚像元定位方法。在该方法中,在现有的基于插值的亚像元定位方法处理路径中加入一条新的处理路径。首先,在新的处理路径中利用全色锐化技术对原始粗高光谱图像的空间分辨率进行改进,通过对改进后的图像进行光谱解混得到新型精细丰度图像。其次,将新路径下产生的新型精细丰度图像与现有路径下的精细丰度图像进行融合,得到具有更多空间-光谱信息的更精细丰度图像。最后,根据更细分数图像的预测值,类别分配方法给每个亚像元分配类标签,得到最终的定位结果。实验结果表明,该方法比现有的基于插值的亚像元定位方法产生具有更高的定位精度。     

多帧超分辨率重建中的图像插值

为了实现多帧超分辨率重建,必须从图像序列中提取子像素信息,因此要求图像的配准精确到子像素级。本文提出了一种超分辨率重建中运动矩阵的构造方法。为了提高矩阵的构造精度,该方法引入图像插值,用性能好但计算量较小的三次插值算子实现插值运算,并比较了三种常用插值核的性能。实验结果表明,选择适当的插值函数不仅不会明显增加计算量,而且可以显著提高矩阵的构造精度,从而大大提高多帧超分辨率重建图像的质量。     

一种新型基于利用全色锐化技术的插值高光谱图像亚像元定位（英文）

利用全色锐化技术提出了一种新型基于插值的高光谱图像亚像元定位方法。在该方法中,在现有的基于插值的亚像元定位方法处理路径中加入一条新的处理路径。首先,在新的处理路径中利用全色锐化技术对原始粗高光谱图像的空间分辨率进行改进,通过对改进后的图像进行光谱解混得到新型精细丰度图像。其次,将新路径下产生的新型精细丰度图像与现有路径下的精细丰度图像进行融合,得到具有更多空间-光谱信息的更精细丰度图像。最后,根据更细分数图像的预测值,类别分配方法给每个亚像元分配类标签,得到最终的定位结果。实验结果表明,该方法比现有的基于插值的亚像元定位方法产生具有更高的定位精度。     

相控红外玫瑰扫描超分辨成像技术

红外玫瑰线扫描亚成像目标识别系统是当今主要的最优末制导系统,但该类系统的成像空间分辨率较低,该文研究了玫瑰扫描参数最优控制准则,提出了扫描初始相位参数控制法,通过改变每帧的初始相位并进行多帧扫描相图重叠,高速高效地形成了高分辨率成像空间。DSP系统实验结果表明,该技术有效地提高了系统的成像空间分辨率。     

光纤耦合的亚像元超分辨率扫描成像图像处理

遥感成像时,采用六角形排列叠层结构的光纤束耦合图像,微扫描工作方式使目标图像依次通过各层光纤。六角形排列的光纤束邻近层光纤之间的错位属亚像元量级,采用亚像元图像处理能获取超分辨率图像。亚像元处理时,首先分离邻近层光纤耦合的图像,以其中一幅图像为基准对另一图像进行配准处理得到中间图像,然后对中间图像和基准图像进行傅里叶变换。考虑仪器及人眼分辨极限,设定图像信号为带限信号,将光纤束邻近层半个像元的错位转化为两幅图像频谱的相位差,从而确定图像融合的插值函数。实验结果表明,针对光纤束六角形排列的亚像元处理获取了超高空间分辨率的图像。     

采用MTF定量评估CCD错位成像的成像质量

为提高CCD错位成像系统成像质量,提出用MTF方法定量评估CCD错位成像的成像质量,推导了CCD错位成像两种模式的MTF,取人眼能分辨的最低对比度0.05为阈值,分析表明,交错采样和四点采样模式的理论极限分辨率分别提高到1.4倍和1.86倍,奈奎斯特频率处MTF值分别提高了0.110 6（27%）和0.167 9（41%）。用空间频率范围（0,0.5）内MTFA评估CCD成像质量,结果表明,交错采样模式和四点采样模式成像质量均优于CCD普通模式,且四点采样模式比交错采样模式成像质量进一步提高。建立了Matlab仿真CCD错位成像的数学模型,鉴别率板仿真结果验证了应用MTF定量评估CCD错位成像系统成像质量的正确性。     

An image registration algorithm based on phase correlation and the classical Lucas–Kanade technique

Image registration is defined as an important process in image processing in order to align two or more images. A new image registration algorithm for translated and rotated pairs of 2D images is presented in order to achieve subpixel accuracy and spend a small fraction of computation time. To achieve the accurate rotation estimation, we propose a two-step method. The first step uses the Fourier Mellin Transform and phase correlation technique to get the large rotation, then the second one uses the Fourier Mellin Transform combined with an enhance Lucas–Kanade technique to estimate the accurate rotation. For the subpixel translation estimation, the proposed algorithm suggests an improved Hanning window as a preprocessing task to reduce the noise in images then achieves a subpixel registration in two steps. The first step uses the spatial domain approach which consists of locating the peak of the cross-correlation surface, while the second uses the frequency domain approach, based on low-frequency (aliasing-free part) of aliased images. Experimental results presented in this work show that the proposed algorithm reduces the computational complexities with a better accuracy compared to other subpixel registration algorithms.     

Temporal integration method for image-processing-basedsuper-high-resolution image acquisition

The authors propose an image processing-based approach towards the development of a super-high-resolution image acquisition system. Imaging methods based on this approach can be classified into two main categories: a spatial integration imaging method and a temporal integration imaging method. With regard to the spatial integration imaging method, the authors have previously presented a method for acquiring an improved-resolution image by integrating multiple images taken simultaneously with multiple different cameras. They develop their work, aiming at a particular class of application where a user indicates a region of interest (ROI) on an observed image in advance, and apply a prototypal temporal integration imaging method. The prototypal temporal integration imaging method does not involve global image segmentation, but uses a subpixel registration algorithm which describes an image warp within the ROI, with subpixel accuracy, as a deformation of quadrilateral patches. The method then performs a subpixel registration by warping an observed image with the warping function recovered from the deformed quadrilateral patches. Experimental simulations demonstrate that the temporal integration imaging is promising as a basic means of high resolution imaging     

Direct comparison of a xenon and a solid-state CT detector system: measurements under working conditions

Measurements of various image quality parameters were carried out with two different detector systems in an otherwise unchanged medical computed tomography (CT) scanner. As all other components of the scanner and the image reconstruction system remained identical, we were able to quantify the difference in performance between a Xenon gas ionization detector and a new solid-state scintillation detector in an isolated fashion. We determined noise, spatial resolution, and artifact behavior and assessed the potential for dose reduction. No significant impact of the detector change on absolute CT values of a calibration phantom was observed. Spatial resolution was improved by more than 10% for the solid-state system. As the system's modulation transfer functions were measured with a wire phantom and otherwise unchanged scanner geometry and image reconstruction algorithm, the increase of resolution is explained by the improved temporal response of the solid-state detector. At the same time, noise was reduced by 12% for a 20-cm diameter water phantom. The noise reduction corresponds to a possible reduction of patient dose by 23% for constant image quality, which is in good agreement with our prediction by estimations of both systems total detective quantum efficiency. Also, a significant improvement of scatter rejection was found for the solid-state system.     

赋形像元探测器在超分辨重建中的应用

大多数光电成像系统的空间分辨率都与探测器的元数密切相关,增加探测器的元数是提高成像系统空间分辨率的核心问题之一.在不增加探测器元数的前提下,提高空间分辨率的技术途径之一就是超分辨重建技术,它通过增加探测器采样频率来提高探测器的空间分辨率.考虑到探测器的空间分辨率并不完全取决于采样作用,且受像元孔径效应的影响,提出了一种赋形像元探测器.基于巴比涅原理中的互补屏原则,将原有的红外探测器中的每个正矩形像元去掉1/4,用剩余部分来等效获取去掉部分的高截止频率;同时利用两列赋形像元探测器进行亚像元推扫,结合像元细分算法,实现超分辨重建.通过同时提高系统采样频率和探测器的截止频率来实现红外系统最终的高分辨率重建成像.     

The Enriched Feature Enhancement Technique for Satellite Image Based on Transforms Using PCNN

The features of the satellite images can be improved by fusing or combining two images with complementary property. By fusing these two images the spatial property of the resultant image is improved. Satellite images are one of the agents that give the features of the earth’s surface. Processing these satellite images will provide more geographical information hidden in the images. This research paper have an detailed insight study of two types of the satellite images one is Panchromatic (PAN) and other Multispectral (MS). The PAN image with high spatial resolution and MS image with spectral resolution are fused to get better resultant output. For fusion process Nonsubsampled Contour let Transform is used to decompose the images into low and high frequency values. Pulse Coupled Neural Network is used to motivate the low frequency pixel and Morphological filter is applied to the edge detected image for finding the features in the images. This is an real time transformations which will give better results in SAR image processing, video processing, stereo based reconstruction of depth and width of the features present in the image.

     

Subpixel variability of remotely sensed soil moisture: aninter-comparison study of SAR and ESTAR

The representation of subpixel variability in soil moisture estimates from passive microwave data was investigated through sensitivity analysis and by comparison against the spatial structure of soil moisture fields derived from radar data. This work shows that the subpixel variability not represented in brightness temperature fields is directly associated with the spatial organization of soil hydraulic properties and the spatial distribution of vegetation. The significant implication of this result is that the physical connection between soil moisture estimates at the pixel scale and local values within the pixel weakens strongly as the sensor resolution decreases. Subsequently, the application of scaling and fractal interpolation principles to downscale passive microwave data to the spatial resolution of radar data was investigated as a means to recover spatial structure. In particular, ESTAR soil moisture data was successfully downscaled from 200 to 40 m using only one radar frequency (e.g., L-band). This application suggests that the combined use of active and passive single-band microwave remote-sensing of soil moisture is a viable approach to improve the spatial resolution of soil moisture remote-sensing     

Polyphase antialiasing in resampling of images.

Changing resolution of images is a common operation. It is also common to use simple, i.e., small, interpolation kernels satisfying some "smoothness" qualities that are determined in the spatial domain. Typical applications use linear interpolation or piecewise cubic interpolation. These are popular since the interpolation kernels are small and the results are acceptable. However, since the interpolation kernel, i.e., impulse response, has a finite and small length, the frequency domain characteristics are not good. Therefore, when we enlarge the image by a rational factor of (L/M), two effects usually appear and cause a noticeable degradation in the quality of the image. The first is jagged edges and the second is low-frequency modulation of high-frequency components, such as sampling noise. Both effects result from aliasing. Enlarging an image by a factor of (L/M) is represented by first interpolating the image on a grid L times finer than the original sampling grid, and then resampling it every M grid points. While the usual treatment of the aliasing created by the resampling operation is aimed toward improving the interpolation filter in the frequency domain, this paper suggests reducing the aliasing effects using a polyphase representation of the interpolation process and treating the polyphase filters separately. The suggested procedure is simple. A considerable reduction in the aliasing effects is obtained for a small interpolation kernel size. We discuss separable interpolation and so the analysis is conducted for the one-dimensional case.