基于正则化方法的图像盲去模糊

针对标准化稀疏先验的正则化方法估计复杂模糊核时的不准确性, 引入图像的预处理, 提出了一种图像盲去模糊的新方法。该方法将图像盲去模糊分为三个步骤：利用双边滤波器和冲击滤波器对图像进行预处理, 使得图像的噪声降低、边缘突出, 有利于模糊核的估计; 对预处理后的图像, 利用基于标准化稀疏先验的正则化方法估计模糊核; 根据估计出的模糊核利用TV正则化方法对图像进行非盲去卷积。采用快速迭代收缩阈值算法和快速总变分图像复原算法分别求解模糊核估计模型和图像非盲去卷积模型。实验结果表明, 针对单幅模糊图像, 该方法可以估计出准确的模糊核, 对噪声具有鲁棒性, 并且提高了图像复原速度, 具有较好的图像恢复效果。     

基于L1与TV正则化的改进图像重建算法

针对不完全投影数据图像重建中出现伪影和噪点的问题,提出了L1与TV同时进行正则化的图像重建模型。基于该重建模型,通过将Bregman迭代和TV软阈值滤波相结合,进一步提出了一种图像重建算法。该算法首先将投影数据通过优化的Bregman迭代算法进行初步重建,然后使用TV软阈值滤波对改造的全变分模型进行二次重建,最后判断是否满足设定的收敛阈值,若满足则结束重建,输出重建图像,否则重复进行上述两步操作,直至迭代完成。实验采用不添加噪声的Shepp-Logan模型与添加噪声的Abdomen模型来验证算法的有效性,证明了所提出的算法在视觉上均优于ART,LSQR,LSQT-STF,BTV等典型的图像重建算法,同时通过多项评价指标对比表明所提出的算法有明显优势。实验结果表明,所提算法在图像重建中能够有效去除条形伪影并保护图像细节,同时具有良好的抗噪性。     

基于L0范数和联合全变分的图像去模糊

为解决图像因各种干扰而模糊的问题,基于典型的正则化约束方法,提出两种图像去模糊正则化模型的图像重建方法。在图像非盲去模糊方面,提出一种基于L0范数和非局部全变分(NLTV)的图像非盲去模糊模型,对图像平滑区和非平滑区分别采用L0范数和NLTV约束,对两个部分采用不同的算法分别求解;在图像盲去模糊方面,提出一种基于L0范数和联合全变分的图像盲去模糊模型,利用L0范数约束求解和模糊核估计方法得到模糊核和潜在图像,用联合全变分对潜在图像求解。实验结果表明,两个模型均有较好的去模糊效果和一定的抗噪鲁棒性。     

基于正则化的超分辨率图像重建方法及其实现

超分辨率图像重建是用同一景物的若干低分辨率图像通过数字图像处理技术获取其高分辨率图像的一种技术.介绍了基于正则化方法的超分辨率图像重建的研究现状和以正则化为基础的几种重建方法在近几年的研究和发展趋势.在此基础上,实现了一种遥感图像的正则化超分辨率重建算法,实验验证了方法的有效性.     

基于双L_0稀疏先验的图像运动去模糊

目前图像的运动去模糊方法在处理较复杂的运动模糊时难以得到理想的效果,其原因之一是这些方法普遍只考虑图像梯度的稀疏性,忽略了模糊核的稀疏性。针对这一不足提出一种新的双L_0正则约束的运动模糊去除方法,该方法同时对自然图像梯度和模糊核使用L_0正则约束,结合半正定二次分裂最小化的方法进行求解优化,实现自然模糊图像梯度和模糊核均稀疏下的模糊核估计,并进一步使用L_(0.5)超拉普拉斯正则约束项恢复最终图像。实验发现,该方法可以较好地去除单幅图像较复杂的运动模糊,更好地克服了估计的模糊核中存在的噪点和错误,得到较现有方法更加理想去模糊效果。     

自适应加权编码L1/2正则化的图像重建算法

针对图像重建过程中噪声去除问题,提出一种自适应加权编码L_1/2正则化重建算法。首先,考虑到许多真实图像中不仅含有高斯噪声,而且含有拉普拉斯噪声,设计一种改进的L₁-L₂混合误差模型(IHEM)算法,该算法兼顾了L₁范数与L₂范数的各自优点;其次,由于迭代过程中噪声分布会发生改变,设计一种自适应隶属度算法,该算法可以减少迭代次数和运算时间;利用一种自适应加权编码方法,该方法可以有效地去除含有重尾分布特性的拉普拉斯噪声;另外,设计一种L_1/2正则化算法,该算法可以得到较稀疏的解。实验结果表明,相比IHEM算法,自适应L_1/2正则化图像重建算法的峰值信噪比(PSNR)平均提高了3.46 dB,结构相似度(SSIM)平均提高了0.02,对含有多种噪声的图像处理具有比较理想的效果。     

基于◢L◣▼1/2▽正则化和局部纹理约束的人脸超分辨率图像重建

为了更好地利用低分辨率人脸图像,提出了一种基于◢L◣▼1/2▽正则化和局部纹理约束的人脸超分辨率重建。在人脸重建的过程中,使用非负矩阵分解将人脸图像放大到合适的中等分辨率,使用局部纹理约束加强纹理特征提取;然后使用局部稀疏先验进行人脸图像重建,再次加入重建约束和局部纹理约束。为了使获取的人脸图像稀疏系数更加稀疏,使用◢L◣▼1/2▽正则化求解稀疏表示系数。实验结果表明,重建的人脸图像保持了原图像的结构,可以实现很好的重建结果,并且具有更好的鲁棒性。     

基于正则化约束的遥感图像多尺度去模糊

目的遥感成像过程中的图像降质严重影响了高分辨率成像与高精度探测,为了改善遥感图像质量,提出了基于正则化约束的遥感图像多尺度去模糊方法。方法首先利用双边滤波器和冲击滤波对遥感图像进行预处理,然后结合遥感图像模糊核的稀疏特性,使用正则化方法迭代求解模糊核最优解,最后利用基于梯度稀疏的非盲反卷积方法得到去模糊结果。此外,针对图像模糊程度较严重的情况,分析了尺度信息对去模糊结果的影响,提出了多尺度迭代优化方法。结果采用本文方法对大量遥感图像进行去模糊,实验结果表明该方法能有效地去除遥感成像产生的模糊,在保持图像边缘和细节的同时,可有效抑制振铃效应。相比其他方法,本文方法恢复图像的边缘强度平均提高28.7%,对比度平均提高17.6%。结论提出一种正则化约束的遥感图像多尺度去模糊方法,主观视觉感受和客观评价指标都表明该方法可以有效提升遥感图像质量。     

基于最小鉴别信息的正则化图像恢复方法

提出在正则化图像恢复方法中将图像恢复结果与先验图像的最小鉴别信息作为新的正则化约束.同传统的正则化约束不同,新的约束使得恢复的图像与给定的先验图像具有最相似的灰度分布.同时给出一种自适应确定正则化参数的方法.实验结果表明,新方法在恢复效果上要优于传统的正则化方法,但对噪声则比较敏感.因此,提出在降质图像含有较多的噪声时保留传统的正则化约束,以达到更好的恢复效果.     

逆主元法盲目复原高斯模糊图像

盲目图像复原的一个重要方法是检测出图像退化的点扩展函数的参数，然后根据估计的点扩展函数复原图像，但是对于高斯模糊的图像，很难检测出其点扩展函数，因此高斯模糊图像的盲复原一直是个棘手问题。本文提出一种新的算法：逆主元法，利用高斯点扩展函数的特性，在径向基神经网络的模型下，对图像进行盲目复原。实验表明，这种方法对轻度的高斯模糊图像，有很好的复原效果。     

Connections between minimum entropy control and mixed 2/ ∞ control for time-varying systems

In this paper two properties of minimum entropy control for linear time-varying systems are investigated. An entropy formulation for anti-causal systems is first considered. Minimizing the norm of an anticausal system is straightforward because of the fact that the norm of an operator is equal to the norm of its adjoint. This is not true for the entropy measure. For this reason a separate formula for the entropy of anti-causal systems is needed in order to consider dual problems that arise in optimal control theory. Secondly, we investigate the relationship between the entropy measure for time-varying systems and the ₂ and _∞ norms. For time-invariant systems, minimum entropy control has been shown to be a good mixed ₂/ _∞ controller. In this paper we show that this is also true in the time-varying case.     

一种基于全变分技术和Lp伪范数的椒盐噪声去除方法

针对传统各向同性全变分（Isotropy total variation,ITV）去噪算法容易导致图像边缘模糊、不易保持图像细节信息等问题,提出一种基于L _p 伪范数和各向同性全变分的图像去噪方法。该方法将L _p 伪范数代替ITV模型中的L ₁范数,利用交替方向乘子算法（Alternating direction method of multipliers, ADMM）将能量泛函拆解成若干个子问题,并将差分算子视为卷积算子;然后引入卷积定理和快速傅里叶变换(Fast Fourier transform, FFT)提高算法运算效率;最后通过Matlab进行仿真实验,运用图像质量的客观和主观评价方法进行评价分析。结果表明,本文方法能够较好地保留图像的边缘特性,有效提升去噪效果。     

结合纹理梯度抑制与L0梯度最小化的纹理滤波

目的 纹理滤波是计算机视觉领域的一个基础应用工具,其目标是抑制图像中不必要的纹理细节和保持图像的主要结构。目前已有的纹理滤波方法多存在强梯度纹理无法被抑制或结构丢失的问题,为此提出一种结合纹理梯度抑制与L₀梯度最小化的纹理滤波算法。方法 首先,提出一种能够区分结构/纹理像素的方向性区间梯度算子,其中采取了局部对比度拉伸和尺度自适应策略,提升了弱梯度结构像素的识别能力。随后,利用区间梯度幅值对原始图像梯度进行抑制,并用抑制后的图像梯度进行图像重建,获得纹理像素梯度小于结构像素梯度的纹理抑制图像。最后,考虑到纹理梯度抑制时会对结构像素的梯度产生一定的衰减作用,本文采用具有梯度提升作用的L₀梯度最小化方法对纹理抑制图像进行滤波,得到纹理抑制结构保持的纹理滤波图像。结果 通过测试马赛克和自然风景等不同类型的图片,并与L₀梯度最小化、滚动引导图像滤波、相对总变分、共现滤波等方法相比较,本文算法能够在抑制强梯度纹理的情况下对图像的主要结构得以保持,并且具有良好的普适性和鲁棒性。同时本文将纹理滤波应用于图像的边缘检测和细节增强,取得了不错的效果提升。结论 本文算法在兼顾强梯度纹理的抑制和结构的保持方面已超越已有的方法,对于图像的目标识别、图像融合、边缘检测等易受强梯度纹理干扰的技术领域,具有较大的应用潜力。     

Minimum ℓ1, ℓ2, and ℓ∞ Norm Approximate Solutions to an Overdetermined System of Linear Equations

Cadzow, J. A., Minimum ℓ₁, ℓ₂, and ℓ_∞ Norm Approximate Solutions to an Overdetermined System of Linear Equations, Digital Signal Processing12 (2002) 524–560Many practical problems encountered in digital signal processing and other quantitative oriented disciplines entail finding a best approximate solution to an overdetermined system of linear equations. Invariably, the least squares error approximate solution (i.e., minimum ℓ₂ norm) is chosen for this task due primarily to the existence of a convenient closed expression for its determination. It should be noted, however, that in many applications a minimum ℓ₁ or ℓ_∞ norm approximate solution is preferable. For example, in cases where the data being analyzed contain a few data outliers a minimum ℓ₁ approximate solution is preferable since it tends to ignore bad data points. In other applications one may wish to determine an approximate solution whose largest error magnitude is the smallest possible (i.e., a minimum ℓ_∞ norm approximate solution). Unfortunately, there do not exist convenient closed form expressions for either the minimum ℓ₁ or the minimum ℓ_∞ norm approximate solution and one must resort to nonlinear programming methods for their determination. Effective algorithms for determining these two solutions are herein presented (see Cadzow, J. A., Data Analysis and Signal Processing: Theory and Applications).     

Influence of doping BiYO3 and Nb2O5 on PTCR characteristics of BaTiO3 thermistor ceramics

Nb₂O₅-doped (1 − x)Ba_0.96Ca_0.04TiO₃-xBiYO₃ (where x = 0.01, 0.02, 0.03 and 0.04) lead-free PTC thermistor ceramics were prepared by a conventional solid state reaction method. X-ray diffraction, scanning electron microscope, Agilent E4980A and resistivity-temperature measurement instrument, were used to characteristic the lattice distortion, microstructure, temperature dependence of permittivity and resitivity-temperature dependence. It was revealed that the tetragonality c/a of the perovskite lattice, the microstructure and the Curie temperature changed with the BiYO₃ content. In order to decrease the room temperature resistivity, the effect of Nb₂O₅ on the room temperature resistivity was also studied, and its optimal doping content was finally chosen as 0.2 mol%. The 0.97Ba_0.96Ca_0.04TiO₃-0.03BiYO₃-0.002Nb₂O₅ thermistor ceramic exhibited a low ρ_RT of 3.98 × 10³ Ω cm, a typical PTCR effect of ρ_max/ρ_min > 10³ and a T_c of 153 °C.     

Electrical response of Sm2O3-doped SnO2 to C2H2 and effect of humidity interference

Pure and Sm₂O₃-doped SnO₂ are prepared through a sol–gel method and characterized by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The sensor based on 6 wt% Sm₂O₃-doped SnO₂ displays superior response at an operating temperature of 180 °C, and the response magnitude to 1000 ppm C₂H₂ can reach 63.8, which is 16.8 times larger than that of pure SnO₂. This sensor also shows high sensitivity under various humidity conditions. These results make our product be a good candidate in fabricating C₂H₂ sensors.     

In2O3 + xBaO (x = 0.5-5 at.%) - A novel material for trace level detection of NOx in the ambient

Indium oxide (In₂O₃) doped with 0.5-5 at.% of Ba was examined for their response towards trace levels of NO_x in the ambient. Crystallographic phase studies, electrical conductivity and sensor studies for NO_x with cross interference for hydrogen, petroleum gas (PG) and ammonia were carried out. Bulk compositions with x ≤ 1 at.% of Ba exhibited high response towards NO_x with extremely low cross interference for hydrogen, PG and ammonia, offering high selectivity. Thin films of 0.5 at.% Ba doped In₂O₃ were deposited using pulsed laser deposition technique using an excimer laser (KrF) operating at a wavelength of (λ) 248 nm with a fluence of ∼3 J/cm² and pulsed at 10 Hz. Thin film sensors exhibited better response towards 3 ppm NO_x quite reliably and reproducibly and offer the potential to develop NO_x sensors (Threshold limit value of NO₂ and NO is 3 and 25 ppm, respectively).     

Synthesis of novel SnO2/ZnSnO3 core-shell microspheres and their gas sensing properities

Large-scale novel core-shell structural SnO₂/ZnSnO₃ microspheres were successfully synthesized by a simple hydrothermal method with the help of the surfactant poly(vinyl pyrrolidone) PVP. The as-synthesized samples were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and high-resolution transmission electron microscopy (HRTEM). The results indicate that the shell was formed by single crystalline ZnSnO₃ nanorods and the core was formed by aggregated SnO₂ nanoparticles. The effects of PVP and hydrothermal time on the morphology of SnO₂/ZnSnO₃ were investigated. A possible formation mechanism of these hierarchical structures was discussed. Moreover, the sensor performance of the prepared core-shell SnO₂/ZnSnO₃ nanostructures to ethanol was studied. The results indicate that the as-synthesized samples exhibited high response and quick response-recovery to ethanol.     

Fabrication of N-type Fe2O3 and P-type LaFeO3 nanobelts by electrospinning and determination of gas-sensing properties

N-type Fe₂O₃ nanobelts and P-type LaFeO₃ nanobelts were prepared by electrospinning. The structure and micro-morphology of the materials were characterized by X-ray diffraction (XRD) and scanning of electron microscopy (SEM). The gas sensing properties of the materials were investigated. The results show that the optimum operating temperature of the gas sensors fabricated from Fe₂O₃ nanobelts is 285 °C, whereas that from LaFeO₃ nanobelts is 170 °C. Under optimum operating temperatures at 500 ppm ethanol, the response of the gas sensors based on these two materials is 4.9 and 8.9, respectively. The response of LaFeO₃-based gas sensors behaves linearly with the ethanol concentration at 10-200 ppm. Sensitivities to different gases were examined, and the results show that LaFeO₃ nanobelts exhibit good selectivity to ethanol, making them promising candidates as practical detectors of ethanol.