Stimulated Raman scattering microscopy with phase-controlled light focusing and aberration correction for rapid and label-free, volumetric deep tissue imaging

We report a novel stimulated Raman scattering(SRS)microscopy technique featuring phase-controlled light focusing and aberration corrections for rapid,deep tissue 3D chemical imaging with subcellular resolution.To accomplish phasecontrolled SRS(PC-SRS),we utilize a single spatial light modulator to electronically tune the axial positioning of both the shortened-length Bessel pump and the focused Gaussian Stokes beams,enabling z-scanning-free optical sectioning in the sample.By incorporating Zernike polynomials into the phase patterns,we simultaneously correct the system aberrations at two separate wavelengths(~240 nm difference),achieving a~3-fold enhancement in signal-to-noise ratio over the uncorrected imaging system.PC-SRS provides>2-fold improvement in imaging depth in various samples(e.g.,polystyrene bead phantoms,porcine brain tissue)as well as achieves SRS 3D imaging speed of~13 Hz per volume for real-time monitoring of Brownian motion of polymer beads in water,superior to conventional point-scanning SRS 3D imaging.We further utilize PC-SRS to observe the metabolic activities of the entire tumor liver in living zebrafish in cellsilent region,unraveling the upregulated metabolism in liver tumor compared to normal liver.This work shows that PCSRS provides unprecedented insights into morpho-chemistry,metabolic and dynamic functioning of live cells and tissue in real-time at the subcellular level.

Image Non-Uniformity Correction in 3T Gd-EOB-DTPA-Enhanced Magnetic Resonance Imaging: Comparison among Different Software Versions

Background: Non-uniformity in signal intensity occurs commonly in magnetic resonance (MR) imaging, which may pose substantial problems when using a 3T scanner. Therefore, image non-uniformity correction is usually applied. Purpose: To compare the correction effects of the phased-array uniformity enhancement (PURE), a calibration-based image non-uniformity correction method, among three different software versions in 3T Gd-EOB-DTPA-enhanced MR imaging. Material and Methods: Hepatobiliary-phase images of a total of 120 patients who underwent Gd-EOB-DTPA-enhanced MR imaging on the same 3T scanner were analyzed retrospectively. Forty patients each were examined using three software versions (DV25, DV25.1, and DV26). The effects of PURE were compared by visual assessment, histogram analysis of liver signal intensity, evaluation of the spatial distribution of correction effects, and evaluation of quantitative indices of liver parenchymal enhancement. Results: The visual assessment indicated the highest uniformity of PURE-corrected images for DV26, followed by DV25 and DV25.1. Histogram analysis of corrected images demonstrated significantly larger variations in liver signal for DV25.1 than for the other two versions. Although PURE caused a relative increase in pixel values for central and lateral regions, such effects were weaker for DV25.1 than for the other two versions. In the evaluation of quantitative indices of liver parenchymal enhancement, the liver-to-muscle ratio (LMR) was significantly higher for the corrected images than for the uncorrected images, but the liver-to-spleen ratio (LSR) showed no significant differences. For corrected images, the LMR was significantly higher for DV25 and DV26 than for DV25.1, but the LSR showed no significant differences among the three versions. Conclusion: There were differences in the effects of PURE among the three software versions in 3T Gd-EOB-DTPA-enhanced MR imaging. Even if the non-uniformity correction method has the same brand name, correction effects may differ depending on the software version, and these differences may affect visual and quantitative evaluations.

A new two-step variational model for multiplicative noise removal with applications to texture images

Multiplicative noise removal problems have attracted much attention in recent years.Unlike additive noise,multiplicative noise destroys almost all information of the original image,especially for texture images.Motivated by the TV-Stokes model,we propose a new two-step variational model to denoise the texture images corrupted by multiplicative noise with a good geometry explanation in this paper.In the first step,we convert the multiplicative denoising problem into an additive one by the logarithm transform and propagate the isophote directions in the tangential field smoothing.Once the isophote directions are constructed,an image is restored to fit the constructed directions in the second step.The existence and uniqueness of the solution to the variational problems are proved.In these two steps,we use the gradient descent method and construct finite difference schemes to solve the problems.Especially,the augmented Lagrangian method and the fast Fourier transform are adopted to accelerate the calculation.Experimental results show that the proposed model can remove the multiplicative noise efficiently and protect the texture well.

Gamma Correction for Brightness Preservation in Natural Images

Due to improper acquisition settings and other noise artifacts,the image degraded to yield poor mean preservation in brightness.The simplest way to improve the preservation is the implementation of histogram equalization.Because of over-enhancement,it failed to preserve the mean brightness and produce the poor quality of the image.This paper proposes a multi-scale decomposi-tion for brightness preservation using gamma correction.After transformation to hue,saturation and intensity(HSI)channel,the 2D-discrete wavelet transform decomposed the intensity component into low and high-pass coefficients.At the next phase,gamma correction is used by auto-tuning the scale value.The scale is the modified constant value used in the logarithmic function.Further,the scale value is optimized to obtain better visual quality in the image.The optimized value is the weighted distribution of standard deviation-mean of low pass coefficients.Finally,the experimental result is estimated in terms of quality assessment measures used as absolute mean brightness error,the measure of information detail,signal to noise ratio and patch-based contrast quality in the image.By comparison,the proposed method proved to be suitably remarkable in retaining the mean brightness and better visual quality of the image.

Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method

In order to find an effective method of detecting thrips defect on green-peel citrus, a defect segmentation method was developed using a single threshold value based on combination of characteristic wavelengths principal component analysis （PCA） and B-spline lighting correction method in this study. At first, four characteristic wavelengths （523, 587, 700 and 768 nm） were obtained using PCA of Vis-NIR （visible and near-infrared） bands and analysis of weighting coefficients; secondarily, PCA was performed using characteristic wavelengths and the second principal component （PC2） was selected to classify images; then, B-spline lighting correction method was proposed to overcome the influence of lighting non-uniform on citrus when thrips defect was segmented; finally, thrips defect on citrus was extracted by global threshold segmentation and morphological image processing. The experimental results show that thrips defect in citrus can be detected with an accuracy of 96.5% by characteristic wavelengths PCA and B-spline lighting correction method. This study shows that thrips defect on green-peel citrus can be effectively identified using hyperspectral imaging technology.

Near field 3-D imaging approach for joint high-resolution imaging and phase error correction

This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error correction. Firstly, a sparse measurement matrix construction method based on a logistic sequence is proposed, which conducts nonlinear transformation for the determined logistic sequence, making it obey uniform distribution, then conducts sign function mapping, and generates the pseudorandom sequence with Bernoulli distribution, thus leading to good signal recovery under down-sampling and easy availability for engineering realization. Secondly, in combination with the RMA imaging approach, the dictionary with all scene information and phase error correction is constructed for CS signal recovery and error correction. Finally, the non-quadratic solution model jointing imaging and phase error correction based on regularization is built, and it is solved by two steps - the separable surrogate functionals (SSF) iterative shrinkage algorithm is adopted to realize target scattering estimate; the iteration mode is adopted for the correction of the dictionary model, so as to achieve the goal of error correction and highly-focused imaging. The proposed approach proves to be effective through numerical simulation and real measurement in anechoic chamber. The results show that, the proposed approach can realize high-resolution imaging in the case of less data; the designed measurement matrix has better non-coherence and easy availability for engineering realization. The proposed approach can effectively correct the phase error, and achieve highly-focused target image. © 2017 Beijing Institute of Aerospace Information.

Nanofabrication of 50 nm zone plates through e-beam lithography with local proximity effect correction for x-ray imaging

High resolution Fresnel zone plates for nanoscale three-dimensional imaging of materials by both soft and hard x-rays are increasingly needed by the broad applications in nanoscience and nanotechnology.When the outmost zone-width is shrinking down to 50 nm or even below,patterning the zone plates with high aspect ratio by electron beam lithography still remains a challenge because of the proximity effect.The uneven charge distribution in the exposed resist is still frequently observed even after standard proximity effect correction(PEC),because of the large variety in the line width.This work develops a new strategy,nicknamed as local proximity effect correction(LPEC),efficiently modifying the deposited energy over the whole zone plate on the top of proximity effect correction.By this way,50 nm zone plates with the aspect ratio from 4:1 up to 15:1 and the duty cycle close to 0.5 have been fabricated.Their imaging capability in soft(1.3 keV)and hard(9 keV)x-ray,respectively,has been demonstrated in Shanghai Synchrotron Radiation Facility(SSRF)with the resolution of 50 nm.The local proximity effect correction developed in this work should also be generally significant for the generation of zone plates with high resolutions beyond 50 nm.

PHASE CORRECTION AND BAND-PASS FILTERS IN CT IMAGING

This paper reports the use of the fast Fourier transform (FFT) in the direct Fourier transform method (DFM) in Computerized Tomography (CT) reconstruction. Phase corrections are needed in the CT reconstruction. In order to eliminate the image distortion from the basic DFM, Padding and band-pass filters are used in the improved DFM. Finally, some reconstructions from simulated projections and several experimental results are given.

FITTING CORRECTION METHOD OF RING ARTIFACTS FOR RECONSTRUCTING CONE-BEAM CT IMAGES

In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often disturb the image quality. A dedicated fitting correction method for high-resolution micro-CT is presented. The method converts each elementary X-ray response curve to an average one, and eliminates response inconsistency among pixels. Other factors of the method are discussed, such as the correction factor variability by different sampling frames and nonlinear factors over the whole spectrum. Results show that the noise and artifacts are both reduced in reconstructed images

X-ray image distortion correction based on SVR

X-ray image has been widely used in many fields such as medical diagnosis,industrial inspection,and so on.Unfortunately,due to the physical characteristics of X-ray and imaging system,distortion of the projected image will happen,which restrict the application of X-ray image,especially in high accuracy fields.Distortion correction can be performed using algorithms that can be classified as global or local according to the method used,both having specific advantages and disadvantages.In this paper,a new global method based on support vector regression（SVR）machine for distortion correction is proposed.In order to test the presented method,a calibration phantom is specially designed for this purpose.A comparison of the proposed method with the traditional global distortion correction techniques is performed.The experimental results show that the proposed correction method performs better than the traditional global one.

Underwater image enhancement based on red channel weighted compensation and gamma correction model

Due to the special characteristics of light in water,the information of the red channel is seriously attenuated in collected image.This causes other colors to dominate the image.This paper proposes an underwater image enhancement algorithm based on red channel weighted compensation and gamma correction model.Firstly,by analyzing the attenuation characteristics of RGB channels,the intensity and the edge information of red channel are compensated by weighting the attenuation coefficient ratio between different channels to correct the chromaticity.Then the gamma correction model is employed to stretch the intensity range to enhance the contrast which makes the image look clearer.The experimental results show that the proposed algorithm can correct the color cast effect and improve the contrast by nearly 2 times for the underwater images with too much red component attenuation.

Movement Invariants-based Algorithm for Medical Image Tilt Correction

In this paper, the edge detection for a medical image is performed based on Sobel operator, and the bounding box is obtained, by which the effective medical sub-image is extracted. Then, the centroid and the normalized central moments of the medical sub-image are calculated, and the rotation angle a is obtained by minimizing the second-order central moment based on its rotation invariance. Finally, the whole medical image is rotated around the centroid by --a to correct the tilted image. F^rthermore, inspired by the uniformity degree of the image, the rotation angle ct is revised, which achieves a better correction effect and performance. The experimental results show that the proposed algorithms are fairly reliable and accurate for the determination of tilt angles, and are practical and effective tilt correction techniques.

A Feasible Atmospheric Correction Method to TM Image

In this paper, an atmospheric correction method to TM image is presented, which can simulate the atmospheric correction parameters, such as optical depth, sky radiance and path radiance at the time the satellite passes,by using interpolation among local meteorological records, parameterization models and dark pixels. The TM image of the Nanjing area in China was corrected by this method. For analyzing the accuracy of this method, the calculated reflectance, apparent reflectance and ground measured reflectance were compared. NDVI before and after atmospheric cor- rection were also compared. The results show that the method is applicable and efficient in the visible to near infrared band of TM image. In order to improve the accuracy of the method, the infrared spectrum measured data for the two other bands of TM image are required in future field investigations. The method is suitable to many other satellite optical remote sensing images with the same or similar spectral characteristics of TM images.

More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of cameras.To enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult.In contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better generalization.Existing self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and artifacts.In response,this paper proposes a self-supervised enhancement method,termed as SLIE.It can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised manner.Illumination attenuation is estimated based on physical principles and local neighborhood information.The removal and correction of noise and color shift removal are solely realized with noisy images and images with color shifts.Finally,the comprehensive and fully self-supervised approach can achieve better adaptability and generalization.It is applicable to various low light conditions,and can reproduce the original color of scenes in natural light.Extensive experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art methods.Our code is available at https://github.com/hanna-xu/SLIE.

A New Correction Algorithm of the Eccentric Ultrasonovision Time Image in the Casing Hole

The ultrasonovision image caused by the tool eccentricity can often present two pieces of vertical black strips in the Casing Well. To solve this problem, this paper proposes a correction algorithm of time eccentricity image based on ellipse fitting algorithm. This algorithm firstly utilizes borehole diameter data to fit ellipse and compute ellipse’s center, major axis, minor axis and inclination angle and other parameters, and then uses these parameters to correct eccentrical ultrasonovision time image. The tested results show that the algorithm can accurately fit ellipse and correct the eccentrical ultrasonovision time image, which is very important practical significance on processing the well logging.

Image Storage and Real-Time Distorted Image Correction by Using Photorefractivity in a Stable Photorefractive Polymer Composite

Using a highly stable and excellently performed three-component photorefractive(PR)polymer composite,poly(N-vinylcarbazole):1-n-butoxyl-2,5-dimethyl-4-(4-nitrophenylazo)benzene:2,4,7-tnnitro-9-fluorenone,optical image storage was demonstrated.The dark storage time was 5-7h.The PR response time was measured to be about 200 ms at an intensity of 1 W/cm^(2) with an applied electric Held of 84 V/μm.A proof-of-principle experiment on real-time correction of distorted images based on phase conjugation of four-wave mixing geometry was also carried out.

Image-based plasma morphology determination and LIBS spectra correction in combustion environments

Spectra correction is essential for the quantification of laser-induced breakdown spectroscopy(LIBS) due to the uncertainties in plasma morphology.In this work,we determined the plasma morphology using a charge-coupled device camera and introduced the spectral correction method based on plasma images to a combustion environment.The plasma length,width,volume,and location were extracted from the plasma images.Using a back-scattering setup,the contribution of plasma location fluctuation to the total spectral fluctuation was mitigated.The integral intensity of the plasma image was used as a proxy of the total number density to correct the spectra.Linear relationships were established between the integral intensities of the plasma images and the spectral intensities,under different laser energy levels and gas temperatures.The image-based correction method could significantly reduce the fluctuation of raw spectral intensities when the laser energy was below 240 mJ.Compared with the correction method based on total spectral areas,the proposed method offered significant improvements in the low energy region,which promises to reduce the signal fluctuations in combustion environments while preserving the spatial resolution and mitigating the flow disturbance.

AN EXPANSION AND CORRECTION ALGORITHM FOR PHOTOELECTRIC IMAGE WITH GEOMETRIC DISTORTION^1

A creepy photoelectric endoscopy system with good performance is studied, and anexpansion and correction algorithm for a compressed photoelectric image with serious geometricdistortion is presented. The algorithm can not only correct the geometric distortion, but alsorestore the gray-level distribution by means of ternary convolution algorithm. The details andthe outline in the image are very clear. It is proved to be of high performance in practice.

Fast Scheme for Projective Geometric Correction and Edge Blending Based on High Dynamic Range Images

With the development of graphic processing unit(GPU)power,it is now possible to implement geometric correction and edge blending functions on a single computer.However,the processing resources consumed by the geometric correction and edge blending phases still burden the system and slow down the main application considerably.A new platform independent scheme is proposed,minimizing the negative influence on performance.In this scheme,parameters for geometric correction and edge blending are firstly defined in an interactive way and recorded as a 32-bit high dynamic range(HDR) image,which is then used by high level shading language(HLSL) codes embedded in the main application as a lookup table,greatly reducing the computational complexity and enhancing flexibility.