Local Brightness Research Articles

A liquid hydrogen tube moderator arrangement for SNS second target station.

Liquid hydrogen filled tubes arranged in a triangular shape surrounded by light-water premoderators were investigated as cold moderators coupled to a neutron production zone of a tungsten target fed by a 1.3 GeV proton beam in a short-pulse mode. A moderator concept optimized for the tube length, premoderator thickness, and target position was found to deliver the highest pulse-integrated neutron brightness suitable to send cold neutron beams for neutron scattering instrumentation geared toward medium resolution and small samples. Reducing the tube diameter from 50 to 10mm boosts the cold neutron brightness (E < 10meV) by a factor of 2.25, also with enhancements seen by downsizing the height of cylindrical moderators in earlier studies. Attempts were made to characterize this novel moderator system with regard to pulse shapes, local brightness distribution, and angular distribution of emission at the neutron emission port.

Multi-Exposure Image Fusion Based on Weighted Average Adaptive Factor and Local Detail Enhancement

In order to adapt to the local brightness and contrast of input image sequences, we propose a new weighted average adaptive factor well-exposure weight evaluation scheme. The exposure weights of brighter and darker pixels are determined according to the local average brightness and expected brightness. We find that in the traditional multi-exposure image fusion scheme, the brighter and darker regions of the scene lose many details. To solve this problem, we first propose a standard to determine the brighter and darker regions and then use a fast local Laplacian filter to enhance the image in the region. This paper selects 16 multi-exposure images of different scenes for subjective and objective analysis and compares them with eight existing multi-exposure fusion schemes. The experimental results show that the proposed method can enhance the details appropriately while preserving the details in static scenes and adapting to the input image brightness.

A new method to estimate 3D cell parameters from 2D microscopy images

Optical microscopy has been a basic and standard technique in cell biology research for decades. Microscopy techniques function well for thin, optically transparent cultures and allow for the imaging of thicker biological specimens. There is no better method of in vitro cell observation and analysis, hence microscopic techniques are extensively used and constitute an optimal tool for cell culture studies. This paper proposes an original methodology of optical microscopy data processing based on the phase contrast technique during cell culture monitoring. By exploiting images recorded during cell proliferation, a surface reconstruction was performed based on assumption, it can be considered that the local brightness of the image depends on the cells' thickness and thus the obtained results can be interpreted in the form of a surface that represents a three-dimensional structure, which allowed for a quantitative description of the cell evolution. The 3D data obtained enabled the investigation of parameters describing the morphology of the cells and the topology of their proliferation. These parameters included cell sizes in plane but also in the direction perpendicular to it, cell volume changes, their spatial distribution, as well as anisotropy and directivity. The method presented provides data carrying information similar to that obtained using a holographic microscope, e.g. A HoloMonitor (Phase Holographic Imaging PHI Inc.), or from confocal scanning microscopy with the “z-stack” mode. The techniques of bright field or phase contrast cell observation are, however, much cheaper, and widely available when compared to holographic microscopy, for instance. Besides, these also enable monitoring of cell activity over time, i.e. the study and quantitative description of dynamic changes in the cells. The proposed approach uses generally available free tools such as ImageJ software with BoneJ and Particle Analyzer plugins. The methodology is suitable for even a basic microscope, it can be easily implemented as a script, and thus data processing can be significantly shortened, the methodology can be automated, and also applied for data processing in real time.

Detection of highly correlated optical and X-ray variations in SS Cygni with Tomo-e Gozen and NICER

Abstract We report on simultaneous optical and X-ray observations of the dwarf nova SS Cyg with Tomo-e Gozen/1.05 m Kiso Schmidt and Neutron star Interior Composition ExploreR (NICER)/International Space Station (ISS). A total of four observations were carried out in the quiescent state and highly correlated light variations between the two wavelengths were detected. We have extracted local brightness peaks in the light curves with a binning interval of 1 s, called “shots,” and have evaluated time lags between the optical and X-ray variations by using a cross-correlation function. Some shots exhibit significant optical lags to X-ray variations and most of them are positive, ranging from +0.26 to +3.11 s, which have never been detected. They may be ascribable to X-ray reprocessing in the accretion disk and/or the secondary star. This analysis is possible thanks to the high timing accuracy and the high throughput of NICER and the matching capability of Tomo-e Gozen. Also, it is confirmed that the correlation between the optical and X-ray variations changed in the middle of one of our observation windows and that the X-ray spectrum softer than 2 keV varied in accordance with the correlation.

Intelligent Clothing Design and Data Acquisition under the Scientific Graphics Programming Combined with Wearable Multisensor

This research focuses on the improvement of intelligent Hanfu design system’s performance. Henceforth, in the current study, an intelligent Hanfu design data acquisition system based on scientific graphics programming and wearable multisensor is designed for the field of human body size measurement and human model reconstruction. Initially, on the basis of wearable multisensor, a design of the recognition and analysis system of human posture is presented. The error of nine-axis inertial sensor in the process of collecting data, the data of accelerometer, gyroscope, and magnetometer are preprocessed, and the processing results are observed. Moreover, MATLAB programming is used for preprocessing of collected images. It is also used for grey normalization, filtering denoising, and image sharpening. The advantages and disadvantages of different methods are compared experimentally. Experiments show that MATLAB programming is more suitable for grey normalization than histogram equalization, and local brightness will appear in histogram equalization. After denoising the image with salt-and-pepper noise and Gaussian noise, the median filter and mean filter have defects. Wiener’s adaptive filter leads to the increase of noise, and wavelet denoising has the best effect. The data acquisition system of intelligent Hanfu design established in this work provides a certain direction for the development of intelligent Hanfu design.

NeuroIV: Neuromorphic Vision Meets Intelligent Vehicle Towards Safe Driving With a New Database and Baseline Evaluations

Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS) using silicon retina are inspired by biological vision, they generate streams of asynchronous events to indicate local log-intensity brightness changes. Their properties of high temporal resolution, low-bandwidth, lightweight computation, and low-latency make them a good fit for many applications of motion perception in the intelligent vehicle. However, as a younger and smaller research field compared to classical computer vision, neuromorphic vision is rarely connected with the intelligent vehicle. For this purpose, we present three novel datasets recorded with DAVIS sensors and depth sensor for the distracted driving research and focus on driver drowsiness detection, driver gaze-zone recognition, and driver hand-gesture recognition. To facilitate the comparison with classical computer vision, we record the RGB, depth and infrared data with a depth sensor simultaneously. The total volume of this dataset has 27360 samples. To unlock the potential of neuromorphic vision on the intelligent vehicle, we utilize three popular event-encoding methods to convert asynchronous event slices to event-frames and adapt state-of-the-art convolutional architectures to extensively evaluate their performances on this dataset. Together with qualitative and quantitative results, this work provides a new database and baseline evaluations named NeuroIV in cross-cutting areas of neuromorphic vision and intelligent vehicle.

Brightness and Saturation Enhancement by Using Color Vector on Equi-Hue Plane in RGB Color Space

In order to improve the image quality of an image with reduced visibility, it is necessary to perform image processing such as brightness correction and sharpening. As a method for improving the visibility of this image, unsharp masking by local projection brightness that emphasizes contrast by using brightness that reflects local color changes while preserving hue has been proposed. In this method, however, block noises are occurred in the image by the excessive emphasis. In this study, we proposed a novel sharpening and saturation enhancement method using an Equi-Hue Plane that has the same hue as the input pixels. The effectiveness of the proposed method has been verified through the various experiments.

Lambertian Model-Based Normal Guided Depth Completion for LiDAR-Camera System

Depth completion is an essential task for the dense scene reconstruction on light detection and ranging (LiDAR)-camera system. Learning-based method achieves precise depth completion results on specific data sets. However, for the general outdoor scenes with insufficient labeled data sets, an efficient nonlearning method is still required. In this letter, from the geometrical constraint between depth and normal, a novel nonlearning normal guided depth completion method is proposed. For the objects in the outdoor scene, local brightness normal (LBN) constraint is derived from the Lambertian model. It is used to recover dense normal from RGB image and sparse normal. After that, we present a pipeline for depth completion with the guidance of dense normal. Extensive experiments on the KITTI depth completion data set demonstrate that our method achieves smaller root mean squared error (RMSE) than current nonlearning methods.

Speckle Reduction in Medical Ultrasound Imaging based on Visual Perception Model

Ultrasound imaging technology is one of the most important clinical imaging modalities due to its safety, low cost, in addition to its versatile applications. The main technical problem in this technology is its noisy appearance due to the presence of speckle, which makes reading imaging more difficult. In this study, a new method of speckle reduction in medical ultrasound images is proposed based on adaptive shifting of the contrast sensitivity function of human vision using a bias field map estimated from the original image. The aim of this work is to have an effective image enhancement strategy that reduces speckle while preserving diagnostically useful image features and allowing practical implementation in real-time for medical ultrasound imaging applications. The new method is used to improve the visual perception of image quality of ultrasound images by adding a local brightness bias to the areas with speckle noise. This allows the variations in image pixels due to speckle noise to be better perceived by the human observer because of the visual perception model. The performance of the proposed method is objectively assessed using quantitative image quality metrics and compared to previous methods. Furthermore, given that image quality perception is subjective, the level of added bias is controlled by a single parameter that accommodates the different needs for different users and applications. This method has potential to offer better viewing conditions of ultrasound images, which translates to higher diagnostic accuracy.

An improved firefly algorithm for identifying parameters of nonlinear empirical models

The nonlinear model is to describe the vortex-induced resonance of long-span bridges under the action of natural wind. The identification accuracy of its parameters directly affects people's understanding of vortex-induced vibration. People have been trying different algorithms to solve this parameter identification problem, but the efficiency and accuracy of algorithms are not satisfied. In this work, a firefly algorithm based on local chaos search and brightness variant (FACLBV) is proposed. The characteristics of chaos make FACLBV search the widely local scope and improve the accuracy of the solution. FACLBV modifies the fixed initial brightness, discards the absorption coefficient of light intensity, links the initial brightness of every firefly with the position of its solution space, and sets the attraction of every firefly as a simple linear function, which reduces the complexity of the algorithm and improves the efficiency. In order to better verify the superiority of FACLBV, the simulation experiment includes three parts: the comparison between FACLBV and other firefly algorithms, the verification of the parameters identified by FACLBV, and the nonparametric test between FACLBV and other intelligent algorithms. Simulation results show that FACLBV is better than other algorithms in performance.

A New Defogging Algorithm for Underwater Images

Abstract Images taken underwater will appear greenish or blueish due to the scattering and attenuation of light, resulting in color distortion of underwater images. This paper proposes a new underwater image defogging algorithm, which can effectively remove image noise, improve the color saturation and contrast of underwater images, and restore clear underwater images without fog. The algorithm introduces guided filtering, which increases speed and work efficiency. The linear enhancement of the saturation component can effectively enhance the color saturation of the underwater image. Compensation for local brightness can better show image details. Through experimental comparison with other algorithms, our algorithm has achieved good advantages in terms of defogging, image structural information integrity, and resistance to color attenuation.

Skin Lesion Detection Algorithms in Whole Body Images

Melanoma is one of the most lethal and rapidly growing cancers, causing many deaths each year. This cancer can be treated effectively if it is detected quickly. For this reason, many algorithms and systems have been developed to support automatic or semiautomatic detection of neoplastic skin lesions based on the analysis of optical images of individual moles. Recently, full-body systems have gained attention because they enable the analysis of the patient’s entire body based on a set of photos. This paper presents a prototype of such a system, focusing mainly on assessing the effectiveness of algorithms developed for the detection and segmentation of lesions. Three detection algorithms (and their fusion) were analyzed, one implementing deep learning methods and two classic approaches, using local brightness distribution and a correlation method. For fusion of algorithms, detection sensitivity = 0.95 and precision = 0.94 were obtained. Moreover, the values of the selected geometric parameters of segmented lesions were calculated and compared for all algorithms. The obtained results showed a high accuracy of the evaluated parameters (error of area estimation <10%), especially for lesions with dimensions greater than 3 mm, which are the most suspected of being neoplastic lesions.

Tunable Wide-Field Illumination and Single-Molecule Photoswitching with a Single MEMS Mirror.

Homogeneous illumination in single-molecule localization microscopy (SMLM) is key for the quantitative analysis of super-resolution images. Therefore, different approaches for flat-field illumination have been introduced as alternative to the conventional Gaussian illumination. Here, we introduce a single microelectromechanical systems (MEMS) mirror as a tunable and cost-effective device for adapting wide-field illumination in SMLM. In flat-field mode the MEMS allowed for consistent SMLM metrics across the entire field of view. Employing single-molecule photoswitching, we developed a simple yet powerful routine to benchmark different illumination schemes on the basis of local emitter brightness and ON-state lifetime. Moreover, we propose that tuning the MEMS beyond optimal flat-field conditions enables to study the kinetics of photoswitchable fluorophores within a single acquisition.

A brightness-adaptive kernel prediction network for inverse tone mapping

The inverse tone mapping (iTM) technique that produces a high dynamic range (HDR) image from one single standard dynamic range (SDR) image has received much attention in industry and academia recently. However, existing methods to recover HDR images mainly focus on overexposed regions but ignore underexposed regions. The underexposed regions in an image are susceptible to noise and artifacts, which will reduce the quality of the image and the user’s visual experience. Therefore, in this paper, we propose a brightness-adaptive iTM model based on deep learning to focus on the content restoration of both the overexposed and underexposed regions in an SDR image simultaneously. In this model, instead of directly predicting the HDR output, we adopt an encoder-decoder network to predict spatially adaptive kernels, which further convolute the input SDR image to produce the HDR result. With the spatially adaptive kernels, the input regions with different exposures can be adaptively mapped by making full use of neighborhood information. Importantly, brightness-adaptive skip connections in the encoder-decoder network, as well as a region loss, are designed to force the proposed model to attach importance to overexposed and underexposed regions. Besides, a global branch is employed in our encoder to exploit both the global and local brightness. Extensive qualitative and quantitative experiments demonstrate that the proposed approach outperforms recent methods on multiple metrics.

Perceived roughness of glossy objects: The influence of Fresnel effects and correlated image statistics.

The roughness of a shiny surface determines how sharp the reflected image of the surroundings is, and thus whether the surface appears highly glossy or more or less matte. In a matching experiment, subjects were asked to reproduce the perceived roughness of a given surface (standard) in a comparison stimulus (match), where the standard and the match could differ in both shape and illumination. To compare the effect of the reflection model on the accuracy of the settings, this was done for two different reflectance models (bidirectional reflectance distribution function [BRDF]). The matching errors were smaller, that is, the constancy under shape and illumination changes higher, when Fresnel effects were physically correctly reproduced in the reflectance model (Fresnel-BRDF) than when this was not the case (Ward-BRDF). The subjects’ settings in the experiment can be predicted very well by two image statistics, one of which is based on the mean edge strength and the other on a local discrete cosine transform. In particular, these predictions also reflect the empirically observed advantage of the Fresnel-BRDF. These results show that the constancy of perceived roughness across context changes may depend on the BRDF used, with Fresnel effects playing a significant role. The good prediction of subjects’ settings using the two image statistics suggests that local brightness variance, which affects both image statistics, can be used as a valid cue for surface roughness.

Multiepoch Optical Images of IRC+10216 Tell about the Central Star and the Adjacent Environment

Abstract Six images of IRC+10216 taken by the Hubble Space Telescope at three epochs in 2001, 2011, and 2016 are compared in the rest frame of the central carbon star. An accurate astrometry has been achieved with the help of Gaia Data Release 2. The positions of the carbon star in the individual epochs are determined using its known proper motion, defining the rest frame of the star. In 2016, a local brightness peak with compact and red nature is detected at the stellar position. A comparison of the color maps between 2016 and 2011 epochs reveals that the reddest spot moved along with the star, suggesting a possibility of it being the dusty material surrounding the carbon star. The relatively red, ambient region is distributed in an Ω shape and corresponds well to the dusty disk previously suggested based on near-infrared polarization observations. In a larger scale, differential proper motion of multiple ring-like patterns in the rest frame of the star is used to derive the average expansion velocity of transverse wind components, resulting in ∼12.5 km s−1(d/123 pc), where d is the distance to IRC+10216. Three-dimensional geometry is implied from its comparison with the line-of-sight wind velocity determined from half widths of submillimeter emission line profiles of abundant molecules. Uneven temporal variations in brightness for different searchlight beams and anisotropic distribution of the extended halo are revisited in the context of the stellar light illumination through a porous envelope with postulated longer-term variations for a period of ≲10 yr.

Study on Local to Global Radiometric Balance for Remotely Sensed Imagery

Due to the difference of factors, such as lighting conditions, shooting environments, and time, there is compound brightness difference between adjacent images, which includes local brightness difference and radiometric difference. This paper proposed a method to eliminate the compound brightness difference of adjacent images after mosaicking, named local to global radiometric balance. It includes the brightness compensation model and brightness approach model. Firstly, the weighted average value of each row and column of image are calculated to express the brightness change; secondly, according to weighted average value, the brightness compensation model is built; thirdly, combined with the blocking method, the brightness compensation model is applied to image. Based on the value after above process, the brightness approach model is established to make the gray value of adjacent images approach to the mosaic line. In the paper, the standard deviation, MSE (mean square error) and mean value are used as the measure indices of the effect of brightness balance. The three groups of experimental results show that compared with the brightness stretch method, the histogram equalization method and the radiometric balance method, the local to global radiometric balance method not only realizes compound brightness balance, but also has better visual effects than others.

Edge-on boxes with X-features as parts of galactic bars

Context. This paper is a contribution to the discussion about whether the X/peanut component is part of the bar, or the bar itself. Aims. Our goal is to present a clear-cut case of a barred-spiral galaxy in which all structural components (i.e. the thick and thin part of the bar and the spiral arms) can be observed in its image and their dimensions directly measured there. Methods. We obtained deep images of the nearby galaxy NGC 352, which has an ideal inclination allowing us to observe all of the parts that compose its morphology, estimate their relative sizes, and determine the topology of the luminous matter of this galaxy. We successfully compare our findings with the existence and the relative dimensions of the corresponding components encountered in the disc of a GADGET N-body model. Results. NGC 352 is a barred spiral galaxy with a bar of about 13 kpc radius. Its bar has a central thick part that extends up to a distance about 5 kpc from the centre of the galaxy along its major axis, while its thickness reaches a height of 3.8 kpc. Thus, the thick part of the bar occupies the central part of the bar component, and its length is about 40% of that of the thin bar. The branches of the X-feature are characterised by the presence of ‘hooks’ at their extremities. The profile along the major axis of the bar is characterised by the presence of ‘shoulders’, the end of which is associated with local surface brightness enhancements on the equatorial plane. A central disc with a spiral-like feature embedded in it dominates in the innermost 1.7 kpc. Conclusions. NGC 352 offers a case in which we directly observe that the X/peanut component is unambiguously part of the bar. This boxy structure is neither a separate bulge component nor the bar itself. The relative extent of the peanut with respect to the bar is well inside the range predicted in the majority of the simulated N-body bars. The hooks of the X-feature and the local surface brightness enhancements on the equatorial plane have their counterparts in surface density features of models based on the orbital theory, as well as of models based on response calculations and of fully selfconsistent N-body calculations.

Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation

Underwater images, which have low contrast and visibility as a result of selective attenuation based on the wavelength of the light passing through water, needs some corrections to extract meaningful information from them. In this paper, we aim to combine two different approaches; global and local contrast enhancement techniques, to obtain better visual quality while enhancing image contrasts on underwater images. While global technique (LDR) ensures the overall enhancement of the image, local technique (CLAHE) considers local brightness features of the image in RGB color space. The proposed method also applies local color correction on underwater image. While methods in the literature apply various approaches on the global histogram of channels, our method divides underwater image into non-overlapping sub-blocks and apply histogram equalization on them. The method uses HSV color space and especially S, V components for color correction. The results of the qualitative analysis show that it produces very good images, in contrast, color, and detail compared to other enhancement methods. The proposed method also decreases the effect of under- and over-enhanced areas and the blue-green effect on the output image. However, the visibility of the objects in the images are increased by color correction. For quantitative analysis, the proposed method produces the highest average value of entropy (7.83), EMEE (32.06), EME (40.97), average gradient (152.55), and Sobel count (130393) for 200 underwater images.

3D surface reconstruction of small height object based on thin structured light scanning

Aiming at the problem of 3D surface reconstruction of small height objects, a method based on the scanning principle with thin structured light is proposed. The laser fringe is produced by a laser light source. It scans the surface of small height object under the control of a precise motion control system, and is integrated with a stereo light microscope and two cameras to form a complete structured light profilometry system. This method is very suitable for 3D surface reconstruction of small height objects. In order to deal with the phenomenon of "cracking" and local uneven brightness in microscope fringe image, the fringe image sequence is captured under different camera exposure parameters, and the quality of fringe image is improved by image fusion. The location of pixels on the center line of laser stripes is detected by the Loess local second-order fitting method, and the positions of these pixels are smoothed and predicted by using the Lowess local linear fitting method. The deformation of the laser stripe center curve is calculated by constructing a baseline, and the 3D surface reconstruction of the object with small height is realized in the image space. Taking the small characters on the surface of Chinese coins and human hair as test samples, their 3D surfaces are constructed by using the method proposed in this paper. The reconstructed 3D surface shapes are highly consistent with the real 3D surface shapes of objects.