彩色图像中颜色不变性和耀斑的分离（Ⅰ）

景物中物体表面的色品是与该物体形状无关的稳定特性,称为颜色不变性。但是,由于耀斑(highlight)和影绸(shading)的存在,图像中对应物体表面点的色品却是变化的,不具有颜色不变性。正确理解图像颜色的基础是建立颜色反射的物理模型。本文叙述了根据Klinker提出的双色反射模型(the dichromatic reflection model),在三维颜色直方图(3D color histogram)中利用K-L变换做平面拟合,分离面反射分量(interface reflection component)和体反射分量(body reflection component),从而计算光源和物体颜色色度坐标的方法,讨论了实际CCD摄像机的局限性,给出了实验结果。     

Optical classification of random image fields using spectral synthetic discriminant functions

It is shown that the problem of classification of images that have the perfectly random nature may be solved with the help of synthetic discriminant functions being synthesized by least-squares technique to separate linearly the power spectra of the corresponding random image fields. The realization of the proposed method by means of an optical technique is discussed, and its efficiency is illustrated by two examples of real-life texture classification.     

Elastic and inelastic scattering components in the angular intensity distribution of He scattered from graphite

The angular intensity distribution of thermal energy He beam scattered from highly oriented pyrolytic graphite (HOPG) surface has been measured by means of supersonic molecular beam scattering technique in the wide surface temperature range. To separate the elastic and inelastic scattering components, simple analysis method has been developed by applying the classical binary collision theory of the hard cube model (HCM). From the extracted elastic scattering component in the scattering distribution, the Debye temperature of the HOPG surface has been derived as 590 ± 30 K. On the basis of the HCM analysis for the extracted inelastic scattering components of He beam, the effective mass for the HOPG surface has been found to be 72 u (six carbon atoms).     

Segmentation of synthetic aperture radar image using multiscale information measure-based spectral clustering

A multiscale information measure （MIM）, calculable from per-pixel wavelet coefficients, but relying on global statistics of synthetic aperture radar （SAR） image, is proposed. It fully exploits the variations in speckle pattern when the image resolution varies from course to fine, thus it can capture the intrinsic texture of the scene backscatter and the texture due to speckle simultaneously. Graph spectral segmen- tation methods based on MIM and the usual similarity measure are carried out on two real SAR images. Experimental results show that MIM can characterize texture information of SAR image more effectively than the commonly used similarity measure.     

空间目标表面材料光谱双向反射分布函数测量与建模

介绍了双向反射分布函数（BRDF）的绝对测量原理和方法,选用光谱分辨率为3 nm的光谱辐射度计及精度为001°的三维转角系统,搭建了BRDF自动测量平台,对空间目标表面包覆材料在400—2500 nm的光谱BRDF进行了测量.结果表明,BRDF曲线极大值所对应的散射角度一般在镜反射方向左右,其余BRDF值随散射角变化很平缓,从中间向两边逐渐变小,近似成余弦分布.测量误差为495%.应用模拟退火算法,结合BRDF五参量统计模型,获得了测量光谱范围内各波长对应的共2101组五参量值,通过对比参量计算结果和 关键词： 双向反射分布函数 绝对测量 误差分析 参量模型     

修正Retinex照射反射模型的彩色图像增强

介绍了修正Retinex照射反射模型的彩色图像增强方法,引入了非线性变换函数修正彩色图像的照射分量和反射分量。由于全局对比度增强函数能够拉伸图像的照射分量,所以改善了全局视觉效果。非线性S型函数对较大和较小的反射分量值改变较小,对中间值改变较大,从而改善了图像的局部对比度。在RGB彩色空间和其他色度亮度彩色空间中的处理结果都没有出现彩色失真的现象。     

一种消除角度响应影响的多波束声强数据自适应改正方法

针对多波束反向散射强度(Backscatter Strength,BS)数据在采集过程中受到声学散射机理而产生的角度响应(Angular Response,AR)影响,而目前声学硬件方面尚未完美解决且现有后处理改正方法在复杂海底底质环境下适应性较差,尤其在高入射角区域的改正效果甚为不理想的问题,为此,给出了一种基于散射强度的自适应角度响应改正模型。首先获取连续脉冲(Ping)平均散射强度数据的角度响应曲线;其次使用高斯拟合方法对角度响应曲线进行平滑拟合处理,进而对其解算二阶导数提取角度响应模型改正参数;最后给出顾及高入射角区域的单Ping反向散射强度数据的分段处理改正模型。实验结果表明,该方法与传统方法相比,整个发射扇区散射强度平均偏差精度约提高30V,尤其在影响较大的高入射角区域,平均偏差精度约提高40V,并且该区域的标准差精度也提高了近30%。该模型较好地解决了多波束在非正射情况下获取海底精准散射声强的问题,削弱了声波散射机理的影响;同时也解决了散射强度过渡不均衡、中央波束区域改正异常等问题。因此,提高了多波束反向散射强度的可靠性,可以真实地呈现出海底实际的地貌。     

Researches on the measurement of distribution image of radiated noise using focused beamforming

A method using focused beamforming to measure the distribution image （underwater image） of submarine and surface ship＇s noise sources is presented. Level linear array can measure the target image on water level, but the multi-path interference of underwater acoustic channel may affect the quality of it. Virtual time reversal mirror and virtual array can both solve the problem very well; they make the image with high resolution.     

Convection and correlation of coherent structure in turbulent boundary layer using tomographic particle image velocimetry

The present experimental work focuses on a new model for space–time correlation and the scale-dependencies of convection velocity and sweep velocity in turbulent boundary layer over a flat wall. A turbulent boundary layer flow at Reθ= 2460 is measured by tomographic particle image velocimetry(tomographic PIV). It is demonstrated that arch, cane,and hairpin vortices are dominant in the logarithmic layer. Hairpins and hairpin packets are responsible for the elongated low-momentum zones observed in the instantaneous flow field. The conditionally-averaged coherent structures systemically illustrate the key roles of hairpin vortice in the turbulence dynamic events, such as ejection and sweep events and energy transport. The space–time correlations of instantaneous streamwise fluctuation velocity are calculated and confirm the new elliptic model for the space–time correlation instead of Taylor hypothesis. The convection velocities derived from the space–time correlation and conditionally-averaged method both suggest the scaling with the local mean velocity in the logarithmic layer. Convection velocity result based on Fourier decomposition(FD) shows stronger scale- dependency in the spanwise direction than in streamwise direction. Compared with FD, the proper orthogonal decomposition(POD) has a distinct distribution of convection velocity for the large- and small-scales which are separated in light of their contributions of turbulent kinetic energy.     

Physical consideration of an image in image restoration using Bayes’ formula

We consider image restoration by Bayes’ formula and investigate the relationship between an image and a prior probability from the following two viewpoints: hyperparameter estimation and the accuracy of a restored image. The Q-Ising model is adopted as a prior probability in Bayes’ formula. Not the Q-Ising energy, but the Potts energy plays an important role in the hyperparameter estimation. From the viewpoint of the hyperparameter estimation, the relationship between a natural image and a prior probability is characterized through the Potts energy and magnetization of an image. The Potts energy and magnetization of an image are defined by a set of pixels’ state of an image. The closer to the average Potts energy and magnetization over a prior probability the Potts energy and magnetization of a natural image is, the closer to the true value of a hyperparameter the estimated value of a hyperparameter from a degraded image is. For the accuracy of a restored image, the image which has a smaller Q-Ising energy is better restored by Bayes’ formula composed of the Q-Ising prior. The consideration for the relationship between an image and a prior probability is expected to be valid for a more complicated prior probability.