Speckle reduction in optical coherence tomography by adaptive total variation method

An adaptive total variation method based on the combination of speckle statistics and total variation restoration is proposed and developed for reducing speckle noise in optical coherence tomography (OCT) images. The statistical distribution of the speckle noise in OCT image is investigated and measured. With the measured parameters such as the mean value and variance of the speckle noise, the OCT image is restored by the adaptive total variation restoration method. The adaptive total variation restoration algorithm was applied to the OCT images of a volunteer’s hand skin, which showed effective speckle noise reduction and image quality improvement. For image quality comparison, the commonly used median filtering method was also applied to the same images to reduce the speckle noise. The measured results demonstrate the superior performance of the adaptive total variation restoration method in terms of image signal-to-noise ratio, equivalent number of looks, contrast-to-noise ratio, and mean square error.     

海洋合成孔径雷达图像斑点噪声的滤除

针对海洋合成孔径雷达(SAR)图像结构信息不明显、水下目标识别困难这一问题,提出了基于经验模式分解(EMD)的算法和H(o)lder指数调整相融合的框架,该框架可以有效地滤除海洋SAR图像的斑点噪声并增强其结构信息,使得人眼可以分辨其特征信息.该融合框架利用EMD将海洋SAR图像分解成不同频率成分的分量,不同层次的分量根据其结构信息和噪声的特征用不同的H(o)lder指数来调整,H(o)lder指数的大小随着分量层数的增加而减小,即在不同尺度下分别抑制斑点噪声,从而恢复其中所包含的结构信息.试验结果表明,利用该框架可以有效抑制SAR图像中的斑点噪声和增强与水下目标相关的结构信息,使人眼可以分辨海洋SAR图像的特征结构.     

基于局部纹理特性和图像分割的分步立体匹配

为解决立体匹配难以兼顾精度和速度的问题,提出一种分步立体匹配方法。根据局部纹理特性对图像对进行灰度变换;然后利用均值漂移算法分割参考图像,以任意大小和形状的分割区域为支持窗口进行初次匹配,形成基于色彩分割的视差约束;再以固定窗口为支持窗口进行二次匹配,获得初始视差图;最后通过可信度分类优化初始视差。实验结果表明所提出的算法兼有较高的匹配速度和精度。     

Markov models of specular and diffuse scattering in restoration ofmedical ultrasound images

Observed medical ultrasound images are degraded representations of the true tissue reflectance. The specular reflections at boundaries between regions of different tissue types are blurred, and the diffuse scattering within such regions also contains speckle. This reduces the diagnostic value of such images. In order to remove both blur and speckle, the authors develop a maximum a posteriori deconvolution algorithm for two-dimensional (2-D) ultrasound radio frequency (RF) images based on a new Markov random field image model incorporating spatial smoothness constraints and physical models for specular reflections and diffuse scattering. During stochastic relaxation, the algorithm alternates steps of restoration and segmentation, and includes estimation of reflectance parameters. The smoothness constraints regularize the overall procedure, and the algorithm uses the specular reflection model to locate region boundaries. The resulting restorations of some simulated and real RF images are significantly better than those produced by Wiener filtering     

基于TV-泊松奇异积分联合先验模型的图像重构

目的针对当前图像重构算法容易产生过渡平滑图像纹理区域,使复原图像丢失大量纹理,降低重构图像视觉质量等缺陷,提出TV-泊松奇异积分联合先验模型耦合贝叶斯推理的图像重构算法。方法引入配分函数,结合TV函数,构造TV图像先验。定义泊松奇异积分先验,并将其嵌入到TV先验中,设计一种联合先验模型,控制图像纹理平滑度。基于高阶统计量技术,完善图像退化模型,并耦合先验模型,生成重构图像的最大后验估计MAP。引入优化最小原则,求解MAP,完成贝叶斯推理,获取重构图像。对文中算法复原图像纹理的关键参数进行优化,并研究分析该算法的用户响应。结果与当前图像重构算法相比,文中算法的复原视觉质量更高,能够较好地平衡噪声与纹理。在图像退化程度较大时,文中算法具有良好的用户响应。结论文中算法能够较好地同步保持图像边缘与纹理。     

Relaxed ordered-subset algorithm for penalized-likelihood image restoration

The expectation-maximization (EM) algorithm for maximum-likelihood image recovery is guaranteed to converge, but it converges slowly. Its ordered-subset version (OS-EM) is used widely in tomographic image reconstruction because of its order-of-magnitude acceleration compared with the EM algorithm, but it does not guarantee convergence. Recently the ordered-subset, separable-paraboloidal-surrogate (OS-SPS) algorithm with relaxation has been shown to converge to the optimal point while providing fast convergence. We adapt the relaxed OS-SPS algorithm to the problem of image restoration. Because data acquisition in image restoration is different from that in tomography, we employ a different strategy for choosing subsets, using pixel locations rather than projection angles. Simulation results show that the relaxed OS-SPS algorithm can provide an order-of-magnitude acceleration over the EM algorithm for image restoration. This new algorithm now provides the speed and guaranteed convergence necessary for efficient image restoration.     

Grinding surface roughness measurement based on the co-occurrence matrix of speckle pattern texture

Surface speckle pattern intensity distribution resulting from laser light scattering from a rough surface contains various information about the surface geometrical and physical properties. A surface roughness measurement technique based on the texture analysis of surface speckle pattern texture images is put forward. In the surface roughness measurement technique, the speckle pattern texture images are taken by a simple setup configuration consisting of a laser and a CCD camera. Our experimental results show that the surface roughness contained in the surface speckle pattern texture images has a good monotonic relationship with their energy feature of the gray-level co-occurrence matrices. After the measurement system is calibrated by a standard surface roughness specimen, the surface roughness of the object surface composed of the same material and machined by the same method as the standard specimen surface can be evaluated from a single speckle pattern texture image. The robustness of the characterization of speckle pattern texture for surface roughness is also discussed. Thus the surface roughness measurement technique can be used for an in-process surface measurement.     

Image speckle noise denoising by a multi-layer fusion enhancement method based on block matching and 3D filtering

In order to improve speckle noise denoising of block matching and 3D filtering (BM3D) method, an image frequency-domain multi-layer fusion enhancement method (MLFE-BM3D) based on nonsubsampled contourlet transform (NSCT) has been proposed. The method designs an NSCT hard threshold denoising enhancement to preprocess the image, then uses fusion enhancement in NSCT domain to fuse the preliminary estimation results of images before and after the NSCT hard threshold denoising, finally, BM3D denoising is carried out with the fused image to obtain the final denoising result. Experiments on natural images and medical ultrasound images show that MLFE-BM3D method can achieve better visual effects than BM3D method, the peak signal to noise ratio (PSNR) of the denoised image is increased by 0.5?dB. The MLFE-BM3D method can improve the denoising effect of speckle noise in the texture region, and still maintain a good denoising effect in the smooth region of the image.     

Filtered backprojection algorithm can outperform iterative maximum likelihood expectation‐maximization algorithm

The iterative maximum‐likelihood expectation‐maximization (ML‐EM) algorithm is an excellent algorithm for image reconstruction and usually provides better images than the filtered backprojection (FBP) algorithm. However, a windowed FBP algorithm can outperform the ML‐EM in certain occasions, when the least‐squared difference from the true image, that is, the least‐squared error (LSE), is used as the comparison criterion. Computer simulations were carried out for the two algorithms. For a given data set the best reconstruction (compared to the true image) from each algorithm was first obtained, and the two reconstructions are compared. The stopping iteration number of the ML‐EM algorithm and the parameters of the windowed FBP algorithm were determined, so that they produced an image that was closest to the true image. However, to use the LSE criterion to compare algorithms, one must know the true image. How to select the optimal parameters when the true image is unknown is a practical open problem. For noisy Poisson projections, computer simulation results indicate that the ML‐EM images are better than the regular FBP images, and the windowed FBP algorithm images are better than the ML‐EM images. For the noiseless projections, the FBP algorithms outperform the ML‐EM algorithm. The computer simulations reveal that the windowed FBP algorithm can provide a reconstruction that is closer to the true image than the ML‐EM algorithm. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 114–120, 2012     

基于 NSCT 域特征和 PCNN 的SAR 图像目标分割

针对 SAR 图像的目标自动分割问题,在分析非下采样轮廓波变换和脉冲耦合神经网络的基础上,提出了一种基于非下采样轮廓波域特征图和 PCNN 的 SAR 图像目标分割算法.对 SAR 图像经过 NSCT 分解后的高、低频图像分别运用不同方式进行处理.对低频图用 PCNN 进行分割以获取目标所在的区域,对高频子带构造了特征图,对特征图利用 PCNN 进行分割以获取目标的精细结构.利用 MSTAR 数据进行了仿真实验,并与基于模糊 C 均值的分割算法、基于马尔可夫随机场的分割算法进行了对比.实验结果表明,所提出算法对 SAR 图像目标的分割结果更为准确,同时较其它算法具有更强的抗噪性能,是一种有效可行的 SAR 目标分割算法.     

一种改进的自然纹理合成方法

自然纹理合成方法是一种适合自然景物的基于样图的快速纹理合成方法。但是候选点超越样图边界的问题没有很好得到解决,成为导致合成后图像产生的纹理块间明显变化的主要因素。论文提出了一种改进的自然纹理合成算法,将样图边缘易产生无效候选点的区域用样图内部与之大小和形状相同的像素块来代替,像素块和被替代像素块沿一条不规则的曲线相匹配。合成过程中在接近边缘时像素块的生长会转向纹理内部。该方法减少了因随机产生候选点而形成的块间不连续,有效地改善了视觉效果。     

Dehazing of remote sensing images using improved restoration model based dark channel prior

Haze degrades visual information of remotely sensed images. Therefore, haze removal is a demanding and significant task for visual multispectral information improvement. The existing haze removal techniques utilize different restrictions and before restoring hazy images in an efficient manner. The review of existing haze removal methods demonstrates that the haze-free images suffer from colour distortion and halo artefacts problems. To solve these issues, an improved restoration model based dark channel prior is proposed in this paper. The proposed technique has redefined transmission map, with the aim to reduce the colour distortion problem. The modified joint trilateral filter is also utilized to improve the coarse estimated atmospheric veil. The experimental results reveal that the proposed approach provides visually significant haze-free images and also preserves the significant detail.     

Richardson-Lucy算法在模糊图像复原中的改进

针对嵌入式系统在采集图像时容易产生模糊图像与Richardson-Lucy复原算法速率较低的问题,提出了Richardson-Lucy结合二维小波变换构建一种微型图像处理模型,并改进了Richardson-Lucy算法来提高模糊图像复原速率,使嵌入式系统对图像处理的速率提高,满足了高实时性要求,处理效果更好,进而达到理想的效果。实验数据证明所设计的复合算法在提高复原速率的同时对图像复原的清晰度有所提升。     

Aberration-free superresolution imaging via binary speckle pattern encoding and processing

We present an approach that provides superresolution beyond the classical limit as well as image restoration in the presence of aberrations; in particular, the ability to obtain superresolution while extending the depth of field (DOF) simultaneously is tested experimentally. It is based on an approach, recently proposed, shown to increase the resolution significantly for in-focus images by speckle encoding and decoding. In our approach, an object multiplied by a fine binary speckle pattern may be located anywhere along an extended DOF region. Since the exact magnification is not known in the presence of defocus aberration, the acquired low-resolution image is electronically processed via a parallel-branch decoding scheme, where in each branch the image is multiplied by the same high-resolution synchronized time-varying binary speckle but with different magnification. Finally, a hard-decision algorithm chooses the branch that provides the highest-resolution output image, thus achieving insensitivity to aberrations as well as DOF variations. Simulation as well as experimental results are presented, exhibiting significant resolution improvement factors.     

Ultrasound Speckle Reduction Based on Histogram Curve Matching and Region Growing

The quality of ultrasound scanning images is usually damaged by speckle noise. This paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing algorithm. Unlike single statistical moment-based speckle reduction algorithms, this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high detectability. The criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in advance. Then, according to the similarity value and tissue characteristics, the entire image is divided into several levels of speckle-content regions, and adaptive smoothing is performed based on these classification characteristics and the corresponding window size determined by the proposed region growing technique. Tests conducted from phantoms and in vivo images have shown very promising results after a quantitative and qualitative comparison with existing work.     

Real-time ultrasound simulation using the GPU

Ultrasound simulators can be used for training ultrasound image acquisition and interpretation. In such simulators, synthetic ultrasound images must be generated in real time. Anatomy can be modeled by computed tomography (CT). Shadows can be calculated by combining reflection coefficients and depth dependent, exponential attenuation. To include speckle, a pre-calculated texture map is typically added. Dynamic objects must be simulated separately. We propose to increase the speckle realism and allow for dynamic objects by using a physical model of the underlying scattering process. The model is based on convolution of the point spread function (PSF) of the ultrasound scanner with a scatterer distribution. The challenge is that the typical field-of-view contains millions of scatterers which must be selected by a virtual probe from an even larger body of scatterers. The main idea of this paper is to select and sample scatterers in parallel on the graphic processing unit (GPU). The method was used to image a cyst phantom and a movable needle. Speckle images were produced in real time (more than 10 frames per second) on a standard GPU. The ultrasound images were visually similar to images calculated by a reference method.     

Generation of photorealistic 3D image using optical digitizer

A technique to generate a photorealistic three-dimensional (3D) image and color-textured model using a dedicated optical digitizer is presented. The proposed technique is started with the range and texture image acquisition from different viewpoints, followed by the registration and integration of multiple range images to get a complete and nonredundant point cloud that represents a real-life object. The accuracy of the range image and the precision of correspondence between the range image and texture image are guaranteed by sensor system calibration. Based on the point cloud, a geometric model is established by considering the connectivity of adjacent range image points. In order to enhance the photorealistic effect, we suggest a texture blending technique that utilizes a composite-weight strategy to blend the texture images within the overlapped region. This technique allows more efficient removal of the artifacts existing in the registered texture image, leading to a 3D image with photorealistic quality and color-texture modeling. Experimental results are also presented to testify to the validity of the proposed method.     

变量分裂机制耦合非循环模糊模型的图像复原

目的针对当前非二次正则化图像复原算法在图像边界的周期拓展难度较大,导致复原图像的边界存在振铃效应,算法的通用性削弱,且时耗严重的问题,提出变量分裂机制耦合非循环卷积模型的抗失真图像快速复原算法。方法引入掩模算子,设计非循环模糊模型,显著消除复原图像的振铃效应;改进数据保真项,构造了最小成本化函数;定义二次辅助变量,嵌入变量分裂策略,设计基于变量分裂的乘数交替方向算法,对非循环模糊模型中的循环与掩模矩阵进行解耦,降低算法复杂度;构造增广拉格朗日函数,耦合交替最小机制与成本函数,以单步封闭式更新估算图像,快速完成图像重构。结果仿真结果显示:与当前复原算法相比,提出算法的失真度最小,且收敛速度更快。结论提出算法能够快速复原多种类型的退化图像,有效消除了复原图像的振铃效应。     

Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture. We use seeded region growing algorithm to ensure texture’s similar local appearance. Secondly, the size and capacity of image can be decreased by introducing the information segmentation, because the capacity of the secret information is proportional to the size of the synthetic texture. Thirdly, enhanced security is also a contribution in this research, because our method does not need to transmit parameters for secret information extraction. LSB is used to embed these parameters in the synthetic texture.     

Application of self-deconvolution method to shift-and-add solar imaging

A shift-and-add (SAA) operation is conducted to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. The self-deconvolving data reconstruction algorithm is used to augment high-spatial-frequency components in solar speckle images and rectify the background component that results from the SAA operation. Self-deconvolved solar speckle images are shift and added and the resulting image shows high-spatial-resolution features.