Novel method for extraction of ship target with overlaps in SAR image via EM algorithm

The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.

Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

A Separating Algorithm for Overlapping Cell Images

The cell overlapping and adhesion phenomenon often exists in cell image processing. Separating overlapped cell into single ones is of great important and difficult in cell image quantitative analysis and automatic recognition. In this paper, an algorithm based on concave region extraction and erosion limit has been proposed to judge and separate overlapping cell images. Experimental results show that the proposed algorithm has a good separation effects on analog cell images. Then the method is applying in actual cervical cell image and obtains good separation result.

A counting method for complex overlapping erythrocytes-based microscopic imaging

Red blood cell(RBC)counting is a standard medical test that can help diagnose various conditions and diseases.Manual counting of blood cells is highly tedious and time consuming.However,new methods for counting blood cells are customary employing both electronic and computer-assisted techniques.Image segmentation is a classical task in most image processing applications which can be used to count blood cells in a microscopic image.In this research work,an approach for erythrocytes counting is proposed.We employed a classification before counting and a new segmentation idea was implemented on the complex overlapping clusters in a microscopic smear image.Experimental results show that the proposed method is of higher counting accuracy and it performs much better than most counting algorithms existed in the situation of three or more RBCs overlapping complexly into a group.The average total erythrocytes counting accuracy of the proposed method reaches 92.9%.

High Order Total Variational Denoising Algorithm Based on l_(0) Overlapping Combination Sparse

For addressing impulse noise in images, this paper proposes a denoising algorithm for non-convex impulse noise images based on the l_(0) norm fidelity term. Since the total variation of the l_(0) norm has a better denoising effect on the pulse noise, it is chosen as the model fidelity term, and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase effect. At the same time, the alternating direction method of multipliers, the majorization–minimization method and the mathematical program with equilibrium constraints were used to solve the model. Experimental results show that the proposed model can effectively suppress the staircase effect in smooth regions, protect the image edge details, and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.

Discussion of overlaped CT image in cerebral function of fossa cranii posterior

AIM:To discuss the value of technique of overlapped CT image in cerebral function of fossa cranii posterior.METHODS:27 cases of diseases of fossa cranii posterior were examined by three techenics(10 mm scan, 6 mm scan, 3mm scan and overlapped image),and then compare the quality of image, accuracy rate of diagnoses, misdiagnosis rate between the three techniques.RESULTS:The quality of image of ovelaped image was better than the other.The accuracy rate of diagnosis were 77.8%, 85.2%and 96.3%.The false positive rate were 14.8%,11.1%and 3.7%.The false negtive rates were 7.4%,3.7%and 0.CONCLUSION:There was important value for diagnosis of diseases of fossa cranii posterior with technique of overlapped CT image,and can provide help for estimation of the cerebral function.

Mass Spectrometric Imaging of Gold Nanolayer Coated Latent Fingermarks: Deciphering Overlapping Features by Statistical Analysis

Overlapping latent fingermarks constitute a serious challenge to database related recognition and matching algorithms in biometry, forensic and crime scene investigations. Mass spectrometry imaging (MSI) is a powerful tool for deciphering and analyzing overlapping fingermarks based on the individual chemical information of each deposit. Fingermark MSI in practice still requires a subjective judgment of an MSI expert, such that rapid analysis, automation, standardization, and a quantitative evaluation of the complete detection and separation process of overlapped fingermarks from MSI data sets is the ultimate goal and will be necessary to become an accepted process in criminal investigations and law enforcement. Here we investigated the feasibility and efficiency of different statistical approaches for the separation of overlapped latent fingermarks based on MSI data. Entropy analysis of generated m/z-images was used to evaluate the results obtained from the statistical analysis. Furthermore, we demonstrate and discuss the opportunity to reconstitute and separate overlapping fingermarks by discrete scanning at selected x,y-positions defined from a previous image analysis using a more simple schema based on visible and therefore optical distinguishable overlapped ink-based fingermarks. The overlapped latent fingermarks were developed by rapid gold sputter coating and analyzed by laser based MSI, without (organic) matrix preparation. Latent finger marks can be transferred from the substrate/surface with and conserved on a soft gold sputtered soft membrane at low temperatures.

SADDLE-POINT BASED SEPARATION OF TOUCHED OBJECTS IN 2-D IMAGE

In many image analysis and processing problems, discriminating the size and shape of each individual object in an aggregate pile projected in an image is an important practice. It is relatively easy to distinguish these features among the objects already separated from each other. The problems will be undoubtedly more complex and of greater challenge if the objects are touched or/and overlapped. This letter presents an algorithm that can be used to separate the touches and overlaps existing in the objects within a 2-D image. The approach is first to convert the gray-scale image to its corresponding binary one and then to the 3-D topographic one using the erosion operations. A template (or mask) is engineered to search the topographic surface for the saddle point, from which the segmenting orientation is determined followed by the desired separating operation. The algorithm is tested on a real image and the running result is adequately satisfying and encouraging.

Image segmentation of overlapping leaves based on Chan–Vese model and Sobel operator

To improve the segmentation precision of overlapping crop leaves,this paper presents an effective image segmentation method based on the Chan–Vese model and Sobel operator.The approach consists of three stages.First,a feature that identifies hues with relatively high levels of green is used to extract the region of leaves and remove the background.Second,the Chan–Vese model and improved Sobel operator are implemented to extract the leaf contours and detect the edges,respectively.Third,a target leaf with a complex background and overlapping is extracted by combining the results obtained by the Chan–Vese model and Sobel operator.To verify the effectiveness of the proposed algorithm,a segmentation experiment was performed on 30 images of cucumber leaf.The mean error rate of the proposed method is 0.0428,which is a decrease of 6.54%compared with the mean error rate of the level set method.Experimental results show that the proposed method can accurately extract the target leaf from cucumber leaf images with complex backgrounds and overlapping regions.

Method for segmentation of overlapping fish images in aquaculture

Individual fish segmentation is a prerequisite for feature extraction and object identification in any machine vision system.In this paper,a method for segmentation of overlapping fish images in aquaculture was proposed.First,the shape factor was used to determine whether an overlap exists in the picture.Then,the corner points were extracted using the curvature scale space algorithm,and the skeleton obtained by the improved Zhang-Suen thinning algorithm.Finally,intersecting points were obtained,and the overlapped region was segmented.The results show that the average error rate and average segmentation efficiency of this method was 10%and 90%,respectively.Compared with the traditional watershed method,the separation point is accurate,and the segmentation accuracy is high.Thus,the proposed method achieves better performance in segmentation accuracy and effectiveness.This method can be applied to multi-target segmentation and fish behavior analysis systems,and it can effectively improve recognition precision.

3D image reconstruction with a controllable overlapping number of elemental images in computational integral imaging

In this Letter, we propose a three-dimensional （3D） image reconstruction method with a controllable overlapping number of elemental images in computational integral imaging. The proposed method can control the overlap- ping number of pixels coming from the elemental images by using the subpixel distance based on ray optics between a 3D object and an image sensor. The use of a controllable overlapping number enables us to provide an improved 3D image visualization by controlling the inter-pixel interference within the reconstructed pixels. To find the optimal overlapping number, we simulate the pickup and reconstruction processes and utilize the numerical reconstruction results using a peak signal-to-noise ratio （PSNR） metric. To demonstrate the feasibility of our work in optical experiments, we carry out the preliminary experiments and present the results.

超高影像重叠度对实景三维建模质量的影响研究

影像重叠度是倾斜摄影测量三维建模的关键指标。本文通过设计定量对比实验,研究超高影像重叠度对实景三维模型质量的影响,并提出相应的内业处理方案。实验结果表明,过高的影像重叠度并未显著提升重建模型的质量,反而损害重建模型的完整度,增加额外的数据处理工作与时间成本。因此,与常规影像重叠度设置相比,采用超高影像重叠度设计的工程效益较差。此结论可为倾斜摄影测量三维建模工程项目提供借鉴与参考。

基于四方向交叠组合稀疏全变分的图像复原

传统全变分具有保存图像特征(边缘、纹理等)优点,但同时也伴随产生阶梯效应。针对此问题,论文提出一种四方向交叠组合稀疏全变分的新模型。首先将每个像素点在四个方向上的梯度信息加以组合,形成组合梯度,充分挖掘图像上四个方向的梯度信息,进一步抑制阶梯效应,全面消除噪声,提高复原后图像的质量,然后利用交替方向乘子算法(AD-MM)将复杂的优化问题分裂为较容易求解的子问题,并使用二维快速傅里叶变换(FFT)和优化最小化算法(MM)交替迭代求解子问题,提高了图像复原的运算速度。

金鲳鱼白点病对其运动轨迹图像重叠的影响

【目的】探明不同密度条件下金鲳鱼白点病发生对其运动轨迹图像重叠的影响,为金鲳鱼的资源保护和深海智慧网箱养殖提供参考。【方法】以健康金鲳鱼和患白点病金鲳鱼为研究对象,采用对比分析法,研究健康和患白点病金鲳鱼的运动轨迹及轨迹图像重叠度变化。【结果】健康金鲳鱼多处于环游状态,运动轨迹为曲线,且随密度增加环游现象明显;患白点病金鲳鱼的环游状态较健康金鲳鱼低,且较长时间段喜停驻在观测水箱角落。健康金鲳鱼的运动轨迹图像重叠度在不同时间较为均匀,随密度增加而增加;患白点病金鲳鱼的运动轨迹图像重叠度不稳定,同组间易出现较大差异。健康金鲳鱼大多时间在中心和边缘区域来回游动,运动频率相对较高,在中心区域停留的时间短,往返频率随密度的增加而增加;患白点病金鲳鱼在中心区域停留的时间较短,进出中心区域的频率低。随试验时间推移,金鲳鱼在中心区域停留的时间延长,进出中心区域的次数减少。【结论】金鲳鱼患白点病后活力减弱,对其运动轨迹、轨迹图像重叠度及在中心区域停留时间均有影响。

基于位置编码重叠切块嵌入和多尺度通道交互注意力的鱼类图像分类

水下鱼类图像分类是一项极具挑战性的任务。传统Vision Transformer(ViT)网络骨干的局限性较大,难以处理局部连续特征,在图像质量较低的鱼类分类中效果表现不佳。为解决此问题,提出一种基于位置编码的重叠切块嵌入(OPE)和多尺度通道交互注意力(MCIA)的Transformer图像分类网络PIFormer(Positional overlapping and Interactive attention transFormer)。PIFormer采用多层级形式构建,每层以不同次数堆叠,利于提取不同深度的特征。首先,引入深度位置编码重叠切块嵌入(POPE)模块对特征图与边缘信息进行重叠切块,以保留鱼体的局部连续特征,并添加位置信息以排序,帮助PIFormer整合细节特征和构建全局映射;其次,提出MCIA模块并行处理局部与全局特征,并建立鱼体不同部位的长距离依赖关系;最后,由分组多层感知机(GMLP)分组处理高层次特征,以提升网络效率,并实现最终的鱼类分类。为验证PIFormer的有效性,提出自建东湖淡水鱼类数据集,并使用公共数据集Fish4Knowledge与NCFM(Nature Conservancy Fisheries Monitoring)以确保实验公平性。实验结果表明,所提网络在各数据集上的Top-1分类准确率分别达到了97.99%、99.71%和90.45%,与同级深度的ViT、Swin Transformer和PVT(Pyramid Vision Transformer)相比,参数量分别减少了72.62×10^(6)、14.34×10^(6)和11.30×10^(6),浮点运算量(FLOPs)分别节省了14.52×10^(9)、2.02×10^(9)和1.48×10^(9)。可见,PIFormer在较少的计算负荷下,具有较强的鱼类图像分类能力,取得了优越的性能。

飞行参数设置对无人机摄影测量建模的影响研究

随着数字基础设施建设的不断推进和数字城市的蓬勃发展,无人机摄影测量建模技术快速兴起。如何在提升模型精度的同时兼顾建模效率问题,受到广泛关注。该文以福州大学宏晖文体综合楼为研究对象,对无人机飞行参数设置与建模效率之间的关系进行量化实验研究。研究结果表明,无人机在旁向重叠率53%、航向重叠率53%、飞行速度9.3 m/s、边距设置为自动时建模效率最佳。

基于边界投射与GPU解析的铁路线路LoD网格场景建模方法

层次细节(LoD)网格地形模型是构建铁路线路三维可视化场景的重要基础。然而,受制于LoD网格模型多层次、多尺度表达的复杂动态特征,以及经典LoD四叉树三维网格地形的独立、分块结构形式,在全球数字地形平台上进行铁路线路建模时,地形裁剪开孔、线路地形融合等环节面临诸多难题。对此,提出全球LoD网格地形上基于外边界投射的铁路线路开孔建模方法,以及利用GPU顶点解析的铁路线路LoD地形动态融合叠置方法,从而实现铁路线路LoD网格地形三维场景高效建模。采取GPU与CPU相结合的办法,首先对地形裁剪区域进行过滤,屏蔽区域内的冗余三角形,留下开孔区域,对区域外围顶点通过投射到区域边缘的修正方式实现点位移动以完成边缘填充,从而避免规则网格上的三角网整合建模,实现复杂地形的规则网格兼容表达。然后,在为地形顶点设置全球统一纹理坐标的基础上,在GPU中对地形纹理与叠置图像分别建立不同的纹理坐标转换关系,实现两者的同模无缝表达,其中针对叠置图像的交互,采用仿射变换的方法突破多重空间非线性变换的困难,解决交互时纹理坐标转换的不同步问题。最终,通过某段184 km铁路线路三维建模案例进行有效性验证。研究结果表明:本文方法可对特定地形区域进行开孔裁剪,再利用GPU顶点解析使铁路线路与LoD地形叠置融合,实现外部铁路模型与真实地形的高效融合,铁路大场景三维建模的渲染效率可由40~70帧提升至55~77帧,优化比率约为30%。

单孔排气气泡特征识别与参数提取方法

气液两相流广泛应用于多种工业领域当中,测量气泡特征参数并进行统计分析可以探究气泡的运动及生长规律,这对相关物理规律和过程控制研究具有重要意义。然而气泡在运动中会发生融合、破碎等现象,导致图像中气泡的重叠粘连,以及拍摄背景的不均匀性均会对气泡特征数据提取造成较大误差。本文采用高速摄像技术获得了不同液体流速与通气量下的气泡图像,通过对距离变换图像的极值点进行抑制与融合,改进了分水岭算法的前景标记提取方法,实现了气泡的准确分割,进而对分割气泡进行最小二乘椭圆拟合重构,获取了气泡参数。对比分析发现,相较于腐蚀运算和阈值分割提取标记的方法,本文方法准确率分别提高了22.7%与13.6%。通过对气泡特征进行统计分析,发现随着通气量的增加,气泡数量略微增多而平均尺寸显著增大,表明通气量对气泡尺寸有着重要影响。通气量相同,随着来流速度的增加,气泡破碎,气泡的数量增加且平均尺寸减小。

基于分数混合阶的交叠组合稀疏全变分HFOGSTV去噪模型

针对全变分(TV)模型引起的阶梯效应,造成图像出现块状伪影的问题,提出了基于分数混合阶的交叠组合稀疏正则项全变分(HFOGSTV)去噪模型。考虑到交叠组合稀疏正则项与分数阶微分能够抑制全局以及局部的块状伪影的特点,将二者引入TV模型,可以较好地抑制阶梯效应。并引入高阶微分,提高模型的去噪效率,构建了基于HFOGSTV去噪模型。新模型采用交替方向乘子法(ADMM)分解为各个子问题进行依次迭代求解,并选择合适的参数。实验结果表明,HFOGSTV模型与非局部均值去噪(NLM)、TV和混合非凸高所交叠组合稀疏全变分(HNHOTV-OGS)模型相比,峰值信噪比(PSNR)分别提升7.2%、5.3%、1.9%,结构相似性(SSIM)分别提升6.6%、6.1%、3.4%,耗时分别减少89%、51%、45%,不仅有效抑制了阶梯效应,而且去噪效果更佳,运行时长大大降低。

Unsupervised Oral Endoscope Image Stitching Algorithm

Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through regis-tration and stitching,which is of great significance for auxiliary diagnosis.Compared with natural images,oral images have lower textures and fewer features.However,traditional feature-based image stitching methods rely heavily on feature extraction quality,often showing an unsatisfactory performance when stitching images with few features.Moreover,due to the hand-held shooting,there are large depth and perspective disparities between the captured images,which also pose a challenge to image stitching.To overcome the above problems,we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features.In the registration stage,we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure.Moreover,we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation.Finally,we reconstruct the stitched images from feature to pixel,which can eliminate artifacts caused by large parallax.Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset.The experimental results show that our algorithm can achieve higher homography estimation accuracy,and better visual quality,and can be effectively applied to oral endoscope image stitching.