A Single Image Derain Method Based on Residue Channel Decomposition in Edge Computing

The numerous photos captured by low-price Internet of Things(IoT)sensors are frequently affected by meteorological factors,especially rainfall.It causes varying sizes of white streaks on the image,destroying the image texture and ruining the performance of the outdoor computer vision system.Existing methods utilise training with pairs of images,which is difficult to cover all scenes and leads to domain gaps.In addition,the network structures adopt deep learning to map rain images to rain-free images,failing to use prior knowledge effectively.To solve these problems,we introduce a single image derain model in edge computing that combines prior knowledge of rain patterns with the learning capability of the neural network.Specifically,the algorithm first uses Residue Channel Prior to filter out the rainfall textural features then it uses the Feature Fusion Module to fuse the original image with the background feature information.This results in a pre-processed image which is fed into Half Instance Net(HINet)to recover a high-quality rain-free image with a clear and accurate structure,and the model does not rely on any rainfall assumptions.Experimental results on synthetic and real-world datasets show that the average peak signal-to-noise ratio of the model decreases by 0.37 dB on the synthetic dataset and increases by 0.43 dB on the real-world dataset,demonstrating that a combined model reduces the gap between synthetic data and natural rain scenes,improves the generalization ability of the derain network,and alleviates the overfitting problem.

Centimeter-sized Cs_(3)Cu_(2)I_(5)single crystals grown by oleic acid assisted inverse temperature crystallization strategy and their films for high-quality X-ray imaging

Low-dimensional halide perovskites have become the most promising candidates for X-ray imaging,yet the issues of the poor chemical stability of hybrid halide perovskite,the high poisonousness of lead halides and the relatively low detectivity of the lead-free halide perovskites which seriously restrain its commercialization.Here,we developed a solution inverse temperature crystal growth(ITCG)method to bring-up high quality Cs_(3)Cu_(2)I_(5)crystals with large size of centimeter order,in which the oleic acid(OA)is introduced as an antioxidative ligand to inhibit the oxidation of cuprous ions effieiently,as well as to decelerate the crystallization rate remarkalby.Based on these fine crystals,the vapor deposition technique is empolyed to prepare high quality Cs_(3)Cu_(2)I_(5)films for efficient X-ray imaging.Smooth surface morphology,high light yields and short decay time endow the Cs_(3)Cu_(2)I_(5)films with strong radioluminescence,high resolution(12 lp/mm),low detection limits(53 nGyair/s)and desirable stability.Subsequently,the Cs_(3)Cu_(2)I_(5)films have been applied to the practical radiography which exhibit superior X-ray imaging performance.Our work provides a paradigm to fabricate nonpoisonous and chemically stable inorganic halide perovskite for X-ray imaging.

Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson’s disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease. Forty-eight Parkinson’s disease patients and 39 matched healthy controls underwent genotyping and 7 T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson’s disease diagnosis. We found that, in Parkinson’s disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein(SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson’s disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroimaging biomarkers in Parkinson’s disease.

Observing single cells in whole organs with optical imaging

Cells are the basic unit of human organs that are not fully understood.The revolutionary advancements of optical imaging alowed us to observe single cells in whole organs,revealing the complicated composition of cells with spatial information.Therefore,in this review,we revisit the principles of optical contrast related to those biomolecules and the optical techniques that transform optical contrast into detectable optical signals.Then,we describe optical imaging to achieve threedimensional spatial discrimination for biological tisutes.Due to the milky appearance of tissues,the spatial information burred deep in the whole organ.Fortunately,strategies developed in the last decade could circumvent this issue and lead us into a new era of investigation of the cells with their original spatial information.

Single exposure passive three-dimensional information reconstruction based on an ordinary imaging system

Existing three-dimensional(3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system.Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional(2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.

R2N: A Novel Deep Learning Architecture for Rain Removal from Single Image

Visual degradation of captured images caused by rainy streaks under rainy weather can adversely affect the performance of many open-air vision systems.Hence,it is necessary to address the problem of eliminating rain streaks from the individual rainy image.In this work,a deep convolution neural network(CNN)based method is introduced,called Rain-Removal Net(R2N),to solve the single image de-raining issue.Firstly,we decomposed the rainy image into its high-frequency detail layer and lowfrequency base layer.Then,we used the high-frequency detail layer to input the carefully designed CNN architecture to learn the mapping between it and its corresponding derained high-frequency detail layer.The CNN architecture consists of four convolution layers and four deconvolution layers,as well as three skip connections.The experiments on synthetic and real-world rainy images show that the performance of our architecture outperforms the compared state-of-the-art de-raining models with respects to the quality of de-rained images and computing efficiency.

A single image dehazing method based on decomposition strategy

Outdoor haze has adverse impact on outdoor image quality,including contrast loss and poor visibility.In this paper,a novel dehazing algorithm based on the decomposition strategy is proposed.It combines the advantages of the two-dimensional variational mode decomposition(2DVMD)algorithm and dark channel prior.The original hazy image is adaptively decom-posed into low-frequency and high-frequency images according to the image frequency band by using the 2DVMD algorithm.The low-frequency image is dehazed by using the improved dark channel prior,and then fused with the high-frequency image.Furthermore,we optimize the atmospheric light and transmit-tance estimation method to obtain a defogging effect with richer details and stronger contrast.The proposed algorithm is com-pared with the existing advanced algorithms.Experiment results show that the proposed algorithm has better performance in comparison with the state-of-the-art algorithms.

An investigation on dissolution kinetics of single sodium carbonate particle with image analysis method

Dissolution kinetics of sodium carbonate is investigated with the image analysis method at the approach of single particle.The dissolution experiments are carried out in an aqueous solution under a series of controlled temperature and p H.The selected sodium carbonate particles are all spherical with the same mass and diameter.The dissolution process is quantified with the measurement of particle diameter from dissolution images.The concentration of dissolved sodium carbonate in solvent is calculated with the measured diameter of particle.Both surface reaction model and mass transport model are implemented to determine the dissolution mechanism and quantify the dissolution rate constant at each experimental condition.According to the fitting results with both two models,it is clarified that the dissolution process at the increasing temperature is controlled by the mass transport of dissolved sodium carbonate travelling from particle surface into solvent.The dissolution process at the increasing pH is controlled by the chemical reaction on particle surface.Furthermore,the dissolution rate constant for each single spherical sodium carbonate particle is quantified and the results show that the dissolution rate constant of single spherical sodium carbonate increases significantly with the rising of temperature,but decreases with the increasing of pH conversely.

Camera Pose Estimation Using Collaborative Databases and Single Building Image

Cities are in constant change and city managers aim to keep an updated digital model of the city for city governance. There are a lot of images uploaded daily on image sharing platforms (as “Flickr”, “Twitter”, etc.). These images feature a rough localization and no orientation information. Nevertheless, they can help to populate an active collaborative database of street images usable to maintain a city 3D model, but their localization and orientation need to be known. Based on these images, we propose the Data Gathering system for image Pose Estimation (DGPE) that helps to find the pose (position and orientation) of the camera used to shoot them with better accuracy than the sole GPS localization that may be embedded in the image header. DGPE uses both visual and semantic information, existing in a single image processed by a fully automatic chain composed of three main layers: Data retrieval and preprocessing layer, Features extraction layer, Decision Making layer. In this article, we present the whole system details and compare its detection results with a state of the art method. Finally, we show the obtained localization, and often orientation results, combining both semantic and visual information processing on 47 images. Our multilayer system succeeds in 26% of our test cases in finding a better localization and orientation of the original photo. This is achieved by using only the image content and associated metadata. The use of semantic information found on social media such as comments, hash tags, etc. has doubled the success rate to 59%. It has reduced the search area and thus made the visual search more accurate.

Compressed Sensing Based on the Single Layer Wavelet Transform for Image Fusion

In this paper, a new method of combination single layer wavelet transform and compressive sensing is proposed for image fusion. In which only measured the high-pass wavelet coefficients of the image but preserved the low-pass wavelet coefficient. Then, fuse the low-pass wavelet coefficients and the measurements of high-pass wavelet coefficient with different schemes. For the reconstruction, by using the minimization of total variation algorithm (TV), high-pass wavelet coefficients could be recovered by the fused measurements. Finally, the fused image could be reconstructed by the inverse wavelet transform. The experiments show the proposed method provides promising fusion performance with a low computational complexity.

10-Bit Single-Slope ADC with Error Calibration for TDI CMOS Image Sensor

A 10-bit single-slope analog-to-digital converter (ADC) for time-delay-integration CMOS image sensor was proposed. A programmable ramp generator was applied to accomplish the error calibration and improve the linearity. The ADC was fabricated in a 180 nm 1P4M CMOS process. Experimental results indicate that the differential nonlinearity and integral nonlinearity were 0.51/-0.53 LSB and 0.63/-0.71 LSB, respectively. The sampling rate of the ADC was 32 kHz.

Infrared Image Denoising Based on Single-wavelet and Multiwavelets

Deviation is essential to classic soft threshold denoising in wavelet domain. Texture features ofnoised image denoised by wavelet transform were weakened. Gibbs effect is distinct at edges of image.Image blurs comparing with original noised image. To solve the questions, a blind denoising method basedon single-wavelet transform and multiwavelets transform was proposed. The method doesn’t depend onsize of image and deviation to determine threshold of wavelet coefficients, which is different from classicalsoft-threshold denoising in wavelet domain. Moreover, the method is good for many types of noise. Gibbseffect disappeared with this method, edges of image are preserved well, and noise is smoothed andrestrained effectively.

Analysis of Object Depth Effects on Accuracy of Dimensional Shape in X and Y Directions Using Single Non-metric Image

一般来说，重建大楼的精确形状，我们为每座大楼需要至少一个立体声模型(二张相片) 。然而，在大多数情况中，仅仅一张单个非公制的相片是可得到的，它是由一个业余运动员的通常获得的任何一个，例如一个旅游者，或从一份报纸或一张明信片。从一幅单个非公制的图象评估 3D 重建的有效性，当这被认为是，这研究借助于模拟法用一幅单个非公制的图象在 X 和 Y 方向在维的形状的精确性上分析目标深度的效果在大多数情况中，在记录并且记录大楼的数据收集的主要来源。

Flexible reduced field of view magnetic resonance imaging based on single-shot spatiotemporally encoded technique

In many ultrafast imaging applications, the reduced field-of-view（r FOV） technique is often used to enhance the spatial resolution and field inhomogeneity immunity of the images. The stationary-phase characteristic of the spatiotemporallyencoded（SPEN） method offers an inherent applicability to r FOV imaging. In this study, a flexible r FOV imaging method is presented and the superiority of the SPEN approach in r FOV imaging is demonstrated. The proposed method is validated with phantom and in vivo rat experiments, including cardiac imaging and contrast-enhanced perfusion imaging. For comparison, the echo planar imaging（EPI） experiments with orthogonal RF excitation are also performed. The results show that the signal-to-noise ratios of the images acquired by the proposed method can be higher than those obtained with the r FOV EPI. Moreover, the proposed method shows better performance in the cardiac imaging and perfusion imaging of rat kidney, and it can scan one or more regions of interest（ROIs） with high spatial resolution in a single shot. It might be a favorable solution to ultrafast imaging applications in cases with severe susceptibility heterogeneities, such as cardiac imaging and perfusion imaging. Furthermore, it might be promising in applications with separate ROIs, such as mammary and limb imaging.

Single pixel imaging based on semi-continuous wavelet transform

Single pixel imaging is a novel imaging technique,and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise.Imaging speed is one of the critical shortcomings,which limits the further development and applications of this technique.In this paper,we focus on the issues of imaging efficiency of a single pixel imaging system.We propose semi-continuous wavelet transform(SCWT)protocol and introduce the protocol into the single pixel imaging system.The proposed protocol is something between continuous wavelet transform and discrete wavelet transform,which allows the usage of those smooth(usually non-orthogonal,and they have advantages in representing smooth signals compressively,which can improve the imaging speed of single pixel imaging)wavelets and with limited numbers of measurements.The proposed imaging scheme is studied,and verified by simulations and experiments.Furthermore,a comparison between our proposed scheme and existing imaging schemes are given.According to the results,the proposed SCWT scheme is proved to be effective in reconstructing a image compressively.

Differential diagnosis of pancreatic cancer by single-shot echo-planar imaging diffusion-weighted imaging

AIM: To investigate the diagnostic ability of single-shot echo-planar imaging(EPI) diffusion-weighted imaging (DWI) to differentiate between malignant and benign pancreatic lesions. METHODS: A computerized search was performed on Pub Med, MEDLINE and EMBASE up to August 2014. Nine studies(10 sets of data) with a total of 304 malignant pancreatic lesions and 188 benign pancreatic lesions were included. The characteristics of each study included the study name, year of publication, magnetic resonance modalities used, patient population, strength of field, pulse time, repetition time, echo time(TE), maximum b factor, mean age, mean body weight, fat suppression, number of benign and malignant lesions, and true positive, true negative, false positive and false negative results. All analyses were performed using Meta-Di Sc and Stata 11.0.RESULTS: The pooled sensitivity and specificity of singleshot EPI DWI were 0.83(95%CI: 0.79-0.87) and 0.77(95%CI: 0.70-0.83), respectively. The positive likelihood ratio and negative likelihood ratio were 5.09(95%CI: 2.19-11.84) and 0.23(95%CI: 0.15-0.36), respectively. The P value for the χ2 heterogeneity for all pooled estimates was < 0.05. From the fitted summary receiver operating characteristic curve, the area under the curve and Q* index were 0.89 and 0.82, respectively. Publication bias was not present(t = 0.58, P = 0.58). Meta-regression analysis indicated that fat suppression, mean age, TE, and maximum b factor were not sources of heterogeneity(all P > 0.05). CONCLUSION: Single-shot EPI DWI is useful to differentiate between malignant and benign pancreatic lesions. Lesion size ≥ 2 cm is the limit for the diagnosis of early lesions.

Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.

Real-Time analysis of exosome secretion of single cells with single molecule imaging

The exosome-mediated response can promote or restrain the diseases by regulating the intracellular pathways,making the exosome become an effective marker for diagnosis and therapeutic control at the single-cell level.However,real-time analysis is hard to be achieved with traditional approaches because the exosomes usually need to be enriched by ultracentrifugation for a measurable signal-to-noise ratio.Recently developed label-free single-molecule imaging approaches may become an real-time quantitative tool for the analysis of single exosomes and related secretion behaviors of single living cells owing to their extreme sensitivity.

ASSESSMENT OF MYOCARDIAL VIABILITY WITH CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING AND COMPARISON WITH SINGLE-PHOTON EMISSION COMPUTED TOMOGRAPHY

客观：与 chronicischemic 心疾病在病人为对心肌的生存能力的评价把提高对比的磁性的回声成像(ceMRI ) 与原子新陈代谢的成像作比较。方法：二十个病人与怀疑长期化学家心疾病经历了单个光子的排放计算了的 ceMRI 和 technetium-99m sestamibi 断层摄影术(SPECT ) 。有积极 SPECT 结果的病人也经历了 18F-fluorodeoxyglucose (FDG ) SPECT。在 a17 片断模型，由 ceMRI 的亢奋的改进(SEH ) 的部分程度由 SPECT 与部分 FDG 和 sestamibi 举起相比。在亢奋的改进 byceMRI 和左室的功能的程度之间的关联被分析。结果：七个病人在 ceMRI 和 technetium-99m sestamibi SPECT 两个都得到了否定结果。剩余的有积极结果的 13 个病人然后经历了 18F-FDG SPECT。在 13 个病人的 221 个片断， SEH 是( 2.1 +/- 8.2 )%，( 25.0 +/- 13.7 )%，并且( 57.7 +/- 23.6 )在有正常新陈代谢/灌注，新陈代谢/灌注失配，和匹配的缺点的片断的%，分别地并且他们中的任何一个二个之间有重要差别(所有 P 【 0.05 )。由操作典型曲线分析的接收装置，在为在可行、不能生存的片断之间的区别的曲线 was0.95 下面的区域。在 34% 的截止价值， SEHoptimally 区分了从 SPECT 定义的不能生存的片断可行。用这阀值， ceMRI 的敏感和特性由 SPECT were92% 定义检测是的不能生存的心肌层并且 93% 分别地。由 ceMRI 的 Hyperenhancement 尺寸与左室的喷射部分否定地被相关(r =- 0.90， P 【 0.01 ) 并且断然与左室的体积(r= 0.62 为结束心脏舒张的体积， r = 0.75 为结束收缩的体积，两 P 【 0.05 ) 。结论: CeMRI 与 chronicischemic 在病人与高精确性允许对心肌的生存能力的评价心疾病。

Single-shot grating-based x-ray differential phase contrast imaging with a modified analyzer grating

X-ray grating interferometer has attracted widely attention in the past years due to its capability in achieving x-ray phase contrast imaging with low brilliance source. However, the widely used phase stepping information extraction method reduces system stability and prolongs data acquisition time by several times compared with conventional x-ray absorption- based imaging. The mechanical stepping can be avoided by using a staggered grating, but at the cost of low vertical spatial resolution. In this paper, employing a modified staggered grating and the angular signal radiography, we proposed a single-shot grating-based x-ray differential phase contrast imaging with decent vertical spatial resolution. The theoretical framework was deduced and proved by numerical experiments. Absorption, phase, and scattering computed tomography can be performed without phase stepping. Therefore, we believe this fast and highly stable imaging method with decent resolution would be widely applied in x-ray grating-based phase contrast imaging.