Pixel Brightness Research Articles

Block-Greedy and CNN Based Underwater Image Dehazing for Novel Depth Estimation and Optimal Ambient Light

A lack of adequate consideration of underwater image enhancement gives room for more research into the field. The global background light has not been adequately addressed amid the presence of backscattering. This paper presents a technique based on pixel differences between global and local patches in scene depth estimation. The pixel variance is based on green and red, green and blue, and red and blue channels besides the absolute mean intensity functions. The global background light is extracted based on a moving average of the impact of suspended light and the brightest pixels within the image color channels. We introduce the block-greedy algorithm in a novel Convolutional Neural Network (CNN) proposed to normalize different color channels’ attenuation ratios and select regions with the lowest variance. We address the discontinuity associated with underwater images by transforming both local and global pixel values. We minimize energy in the proposed CNN via a novel Markov random field to smooth edges and improve the final underwater image features. A comparison of the performance of the proposed technique against existing state-of-the-art algorithms using entropy, Underwater Color Image Quality Evaluation (UCIQE), Underwater Image Quality Measure (UIQM), Underwater Image Colorfulness Measure (UICM), and Underwater Image Sharpness Measure (UISM) indicate better performance of the proposed approach in terms of average and consistency. As it concerns to averagely, UICM has higher values in the technique than the reference methods, which explainsits higher color balance. The μ values of UCIQE, UISM, and UICM of the proposed method supersede those of the existing techniques. The proposed noted a percent improvement of 0.4%, 4.8%, 9.7%, 5.1% and 7.2% in entropy, UCIQE, UIQM, UICM and UISM respectively compared to the best existing techniques. Consequently, dehazed images have sharp, colorful, and clear features in most images when compared to those resulting from the existing state-of-the-art methods. Stable σ values explain the consistency in visual analysis in terms of sharpness of color and clarity of features in most of the proposed image results when compared with reference methods. Our own assessment shows that only weakness of the proposed technique is that it only applies to underwater images. Future research could seek to establish edge strengthening without color saturation enhancement.

Cystic (including atypical) and solid breast lesion classification using the different features of quantitative ultrasound parametric images.

The amount of ultrasound (US) breast examinations continues to grow rapidly because of the wider endorsement of breast cancer screening programs. Cysts are the most commonly diagnosed breast lesions. Atypical breast cysts can be a serious differentiation problem in the US. Our goal was to develop noninvasive automated US grayscale image analysis for the cystic and solid breast lesion differentiation based on mathematical image post-processing. We used a set of 217 ultrasound images of proven 107 cystic (including 53 atypical) and 110 solid lesions. Empirical statistical and morphological models of the lesions were used to obtain features. The AUC indicator and Student's t test were used to assess the quality of the individual features. The Pearson correlation matrix was used to calculate the correlation between various features. The LASSO and stepwise regression methods were used to determine the most significant features. Finally, the lesion classification was carried out by the various methods. The use of LASSO regression for the feature selection made it possible to select the most significant features for classification. The sensitivity increased from 87.1% to 89.2% and the specificity-from 92.2 to 94.8%. After the correlation matrix construction, it was found that features with a high value of the correlation coefficient (0.72; 0.75) can also be used to improve the quality of the classification. The construction of the empirical model of the lesion pixels brightness behavior can provide parameters that are important for the correct classification of ultrasound images. The optimal set of features with the maximum discriminant characteristics may not be consistent with the correlation of features and the value of the AUC index. Features with a low AUC index (in our case 0.72) can also be important for improving the quality of the classification.

Relation between the Severity of the Sensorimotor Cortical Edema with Cell Swelling and the Duration of Common Carotid Artery Occlusion in Rats (Morphometric Study)

The aim of the study. To examine the changes in structure and morphometry in sensorimotor cortical edema with cell swelling in mature white rats after common carotid artery occlusion of various durations.Material and methods. Acute ischemia was modeled on white adult Wistar rats by 20-, 30- and 40-min occlusion of the common carotid arteries (CCA). Histological (hematoxylin-eosin and Nissl staining), immunohistochemical (NSE, MAP-2, GFAP) and morphometric methods were used. Morphometry was assessed on hematoxylin and eosin-stained specimens using ImageJ 1.53 plug-ins (Find Maxima, Find Foci). Statistical hypothesis testing (nonparametric criteria) was performed using Statistica 8.0 software.Results. In the sensorimotor cortex (SMC) of white rats after 20, 30 and 40 minutes of CCA occlusion the signs of cytotoxic brain edema appeared, focal destructive and adaptive changes of neurons and astroglia evolved. The edema persisted throughout the observation period (7 days). The increase in the relative area, the number of cell swelling zones and their hydration (pixel brightness) was significant. On days 1 and 3 after CCA occlusion, some of the SMC astrocyte processes underwent destruction. Subpial and perivascular zones suffered to a greater extent. Mild and moderate (after unilateral 30-min CCA occlusion) to moderate and severe (after bilateral 40-min CCA occlusion) scattered structural and functional changes of the SMC with large areas of clearing in the «porous» neuropil, severe perivascular and perineuronal edema of the astrocyte processes developed. The latter was associated with a moderate reduction of the total neuronal density.Conclusion. After occlusion of CCA, signs of edema with cellular swelling appeared in the SMC amid dystrophic and necrotic pyramidal neurons and activated neuroglial cells. To a greater extent, the signs of brain swelling were evident three days after bilateral 40-min occlusion of CCA.

Integration of Geological, Geochemical, Mineralogical and Remote Sensing Data for Studying Zeolite Deposits of Al-Ahyuq-Taiz, Yemen

Abstract: Zeolite deposits crop out at Al-Ahyuq area, and lies at about 89 km southwest of Taiz city. It is one of the most important zeolite localities in Yemen. The study area is covered by the Yemen volcanic group. X-Ray Diffraction (XRD) analyses showed that clinoptilolite is the major type of Al-Ahyuq zeolites with high purity. Chemical analysis shows that the studied zeolitic tuff samples have silica content ranging from 63.10 wt% - 71.1wt% with an average 68.69 wt%, Fe2O3 [as total iron] with an average 2.38wt%, MgO with an average 0.44 wt% and TiO2 with an average 0.17wt%. These chemical properties of Al-Ahyuq zeolite deposits are with low impurities content such as CaO and MgO, compared to those deposits found in other countries around the world. The chemical and mineralogical studies support that the zeolite minerals of the Al-Ahyuq area formed by subaerial hydrothermal alteration of the parent volcanic glass. The ASTER bands as false colour composite (1-R, 2-G, 3-B), and band ratios 3/9 and 4/6 highlighted area of zeolite deposits dominated as bright pixels. The band ratio combination 4/6-R, 2/1-G and 3/2-B is effective in mapping of Al-Ahyuq zeolitic tuffs. Spectra after being resampled to ASTER VNIR+SWIR bands of the study area comparing with the USGS library spectra of zeolite – clinoptilolite shows almost identical and confirmed that clinoptilolite is the major of zeolite deposits in Al-Ahyuq area. Chemical and mineralogical investigation of the Al-Ahyuq zeolite (clinoptilolite) deposits recommends many important agricultural, environmental, and industrial applications. Keyword: Zeolitic tuff; clinoptilolite; XDR; XRFS; ASTER data; band ratio

Image Analysis of Flow Maldistribution during Boiling in Parallel Minichannels

AbstractThe boiling flow of distilled water with reverse flow in three parallel, rectangular, horizontal minichannels was investigated. The analyzed data was in the form of a set of video frames. An image analysis and statistical analysis of changes of pixel brightness in minichannels was conducted. A self‐organizing process was identified for short slug flow in neighboring minichannels. The identified synchronization process was accompanied by the increase in standard deviation of pixel brightness changes. The process of synchronization was observed for short slugs, but not for long slugs. It can be concluded that the synchronization of heat and mass transfer in minichannels can be achieved when the character of two‐phase flow patterns in each channel is not fully blocking the flow.

Cleaning Images with Gaussian Process Regression

Abstract Many approaches to astronomical data reduction and analysis cannot tolerate missing data: corrupted pixels must first have their values imputed. This paper presents astrofix, a robust and flexible image imputation algorithm based on Gaussian process regression. Through an optimization process, astrofix chooses and applies a different interpolation kernel to each image, using a training set extracted automatically from that image. It naturally handles clusters of bad pixels and image edges and adapts to various instruments and image types. For bright pixels, the mean absolute error of astrofix is several times smaller than that of median replacement and interpolation by a Gaussian kernel. We demonstrate good performance on both imaging and spectroscopic data, including the SBIG 6303 0.4 m telescope and the FLOYDS spectrograph of Las Cumbres Observatory and the CHARIS integral-field spectrograph on the Subaru Telescope.

Detection of Subclinical Keratoconus With a Validated Alternative Method to Corneal Densitometry.

PurposeTo enhance the current standards of subclinical keratoconus screening based on the statistical modeling of the pixel intensity distribution of Scheimpflug images.MethodsScheimpflug corneal tomographies corresponding to 25 corneal meridians of 60 participants were retrospectively collected and divided into three groups: controls (20 eyes), subclinical keratoconus (20 eyes), and clinical keratoconus (20 eyes). Only right eyes were selected. After corneal segmentation, pixel intensities of the stromal tissue were statistically modeled using a Weibull probability density function from which parameter α (pixel brightness) was derived. Further, data were transformed to polar coordinates, smoothed, and interpolated to build a map of the corneal α parameter. The discriminative power of the method was analyzed using receiver operating characteristic curves.ResultsThe proposed platform-independent method achieved a higher performance in discriminating subclinical keratoconus from control eyes (90.0% sensitivity, 95.0% specificity, 0.97 area under the curve [AUC]) than the standard method (Belin–Ambrósio enhanced ectasia display), which uses only corneal morphometry (85.0% sensitivity, 85.0% specificity, 0.80 AUC).ConclusionsAnalysis of light backscatter at the cornea successfully discriminates subclinical keratoconus from control eyes, upgrading the results previously reported in the literature.Translational RelevanceThe proposed methodology has the potential to support clinicians in the detection of keratoconus before showing clinical signs.

Лазерное сканирование и аэро- фотосъемка с БПЛА в исследовании структуры лесотундровых древостоев Хибин

Studying the structure of stands is a key point in assessing the role of trees in carbon deposition. Information on the spatial structure of ground vegetation at the upper treeline is still insufficiently presented in modern studies. High resolution remote sensing can provide important data to understand the properties and dynamics of vegetation in these conditions. We test the applicability of ground-based mobile laser scanning of the terrain and aerial photography for the rapid and high-precision assessment of the characteristics of tree stands in the forest-tundra ecotone. We obtained canopy height models (CHMs) of the forest and supplemented them with aerial photographs of the research area on the southeastern slope of the Khibiny Mountains. Using CHMs we have delineated boundaries of tree crowns. The height and projection area were determined for each tree. The first characteristic obtained by laser scanning was compared to the heights of the same trees estimated by field measurements. This was done for the purposes of verification. The comparison revealed that laser scanning data allow to set heights closest to field measurements in case the heights are determined by the maximum values of brightness of pixels of CHMs with manual correction of values when outliers are detected (R2 = 0.84). Since manual correction of outliers is time-consuming, we proposed a way to automate the measurements by determining tree heights using the sum of the average value of pixel brightness and the standard deviation multiplied by 2.5 (R2 = = 0.79). We compared the area characteristics of the stands obtained by laser scanning and the unmanned aerial vehicle (UAV) photography. Thus, we obtained detailed information on the spatial location and size of 4424 trees in an area of about 10 ha and compared the results of measuring tree characteristics obtained by different methods. It was also found that with increasing height from 290 to 425 m above sea level on the studied slope, the average height of stands decreases gradually from 4.5–5.0 to 1.1–1.6 m with small fluctuations (0.2–0.4 m), while the density of stands changes from 4620–5860 to 145 m2/ha in a non-linear way.

Division of images into areas of local extrema with a monotonic change in pixel brightness

In this paper, the problem of segmentation of halftone images is considered, in which areas of local maxima and minima (extrema) are distinguished with a monotonic change in the brightness of pixels from local extrema to the boundaries of areas. To solve this problem, a mathematical model is proposed and a segmentation algorithm is developed on the basis of counter-wave growing of local extremum regions. The developed algorithm differs from the known segmentation algorithms by using a set of brightness thresholds (by the number of regions), varying by one in each cycle, starting from the values of local extrema, taking into account the increase or decrease in brightness to select adjacent pixels that are attached to the regions formed from these local extrema. The algorithm provides a greater deviation of pixel brightness from the average value within the region compared to known segmentation algorithms. This does not allow evaluating its efficiency using known indicators based on the variance of the brightness within the region. In this regard, estimates of the monotonicity of changes in the brightness of regions are proposed based on a) the shortest distances from each pixel of the region to the corresponding local extremum along the routes determined by the maximum increase (for the region of the local maximum) or decrease (for the region of the local minimum) the brightness of pixels and b) taking into account the number pixels that break the monotony of the segment brightness change. Using these estimates, it is shown that the proposed algorithm provides segmentation of artificial and natural grayscale images with a monotonic change in the brightness of pixels in the areas of local extrema. These properties allow us to consider the developed algorithm as a basis for the selection of texels, spots, low-contrast objects in images.

AN AUTOMATIC EXTRACTION METHOD FOR ANTARCTIC SUBGLACIAL LAKE BASED ON RADIO ECHO SOUNDING DATA

Abstract. Detection of subglacial lakes and interpretation their hydrological connectivity is of great importance to understanding the mass balance of Antarctic ice sheet. Over the past five decades, a large number of Radio Echo Sounding (RES) data has been collected in Antarctica. However, the identification of subglacial lakes based on RES data mainly relies on visual interpretation due to the lack of quantitative indicators for subglacial lakes distinguishing. To solve this problem, an automatic subglacial lakes detection method based on the reflective characteristics of B-scan echogram is proposed in this paper. Firstly, the echo strength of the original radar echogram is corrected for the dielectric attenuation and geometric spreading in the ice. Secondly, the original radar echogram is binarized to preserve the bright subglacial lake region, and the thickness of bright pixels is measured along the direction of A-scan. Thirdly, the thickness, the variance of the thickness in the neighbourhood and the corrected echo strength are used to obtain the response value for the subglacial lake. Finally, a threshold for the response value is determined to detect subglacial lakes. It is found that the proposed method can determine the location of the subglacial lake in Antarctica's Gamburtsev Province (AGAP) region with high accuracy.

Image de-blurring Model based on Machine Learning

Due to the influence of haze in winter, outdoor images usually lose contrast and fidelity. In view of the fact that most de-fog algorithms are not effective for images with large sky areas, an improved dark channel a priori de-fog method is proposed. First of all, the sky region is segmented according to the image gradient information, and on the basis of sky segmentation, the atmospheric light value is reasonably estimated by setting the discriminant formula combined with the high brightness and smoothness of atmospheric light reference pixels. Secondly, according to the different dark channel values, the piecewise linear function is used to dynamically modify the adjustable parameters to solve the local shadow caused by excessive defog. Then, the transmittance estimated by the bright channel model and the improved dark channel prior model are fused, and the edge is optimized by guided filtering. Finally, combined with the atmospheric scattering model, the defog image is obtained by brightness compensation and contrast stretching. The experimental results show that the improved method can effectively improve the image distortion, enhance the image contrast and details, especially in maintaining the visual authenticity of the sky region.

Compensating Nonuniform OLED Pixel Brightness in a Vertical Blanking Interval by Learning TFT Characteristics

Changes in thin-film transistor (TFT) characteristics can cause nonuniform brightness in organic light-emitting diode (OLED) displays, and external compensation circuits cannot address such changes if they occur rapidly. Our system acquires a short segment of the source voltage curve of the TFT driving each pixel, during the vertical blanking interval. It then estimates the threshold voltage ${V}_{\text {th}}$ and the mobility-related parameter ${k}$ of that TFT, using neural networks and recurrent conditional (RC) learning to perform expectation–maximization (EM). Finally, it corrects the pixel brightness accordingly. The average errors in the estimated ${V}_{\text {th}}$ and ${k}$ are, respectively, 7.3 mV and ${3.7} \times {10}^{-{11}}\,\,\text {F}/\text {V}\text {s}$ , and we demonstrate the visual effect of compensating with these estimates.

Improving noise immunity of homography superposition for television signals

The algorithm of homography superposition of the television signals was shown in this article. The algorithm allows improving noise immunity for homography parameters of television signal with textural fragments. The core of the estimation procedure of homography parameters for image superposition is the matching of the feature points. The feature points are local extremes of the pixel brightness of the image. The matching is defined by the maximum correlation coefficient between a region of the image of a neighbor area of the feature point. The log-polar system of the images provides an invariant correlation of scale and rotate are proportional offsets along the axis in this coordinate system. The noise immunity is provided due to the developing procedure of removing feature points in the textural region. This procedure leads to decreasing probability of error matching of the feature points. The numerical modeling shows high noise immunity of the developed procedure in comparing the current researches.

Semiquantitative score of breast arterial calcifications on mammography (BAC-SS): intra- and inter-reader reproducibility.

Breast arterial calcifications (BAC), representing Mönckeberg's sclerosis of the tunica media of breast arteries, are an imaging biomarker for cardiovascular risk stratification in the female population. Our aim was to estimate the intra- and inter-reader reproducibility of a semiquantitative score for BAC assessment (BAC-SS). Consecutive women who underwent screening mammography at our center from January 1st to January 31st, 2018 were retrieved and included according to BAC presence. Two readers (R1 and R2) independently applied the BAC-SS to medio-lateral oblique views, obtaining a BAC score by summing: (I) number of calcified vessels (from 0 to n); (II) vessel opacification, i.e., the degree of artery coverage by calcium bright pixels (0 or 1); and (III) length class of calcified vessels (from 0 to 4). R1 repeated the assessment 2 weeks later. Scoring time was recorded. Cohen's κ statistics and Bland-Altman analysis were used. Among 408 women, 57 (14%) had BAC; 114 medio-lateral oblique views were assessed. Median BAC score was 4 [interquartile range (IQR): 3-6] for R1 and 4 (IQR: 2-6) for R2 (P=0.417) while median scoring time was 156 s (IQR: 99-314 s) for R1 and 191 s (IQR: 137-292 s) for R2 (P=0.743). Bland-Altman analysis showed a 77% intra-reader reproducibility [bias: 0.193, coefficient of repeatability (CoR): 0.955] and a 64% inter-reader reproducibility (bias: 0.211, CoR: 1.516). Cohen's κ for BAC presence was 0.968 for intra-reader agreement and 0.937 for inter-reader agreement. Our BAC-SS has a good intra- and inter-reader reproducibility, within acceptable scoring times. A large-scale study is warranted to test its ability to stratify cardiovascular risk in women.

9‐5: Picosecond‐Laser Blackening of TFT Side Films: A New Technology for Bright‐Pixel Repair

In this paper, for the first time, picosecond laser was used to blacken the TFT side of LCD panel pixels. And this is a new technology to repair the bright pixel. The purpose of shading was successfully realized and the effect of darkening was achieved. And through a series of characterization to explore the mechanism of film darkening: laser through the TFT substrate glass, a part of the ITO film falls off and is formed by the laser impact into the Si3Nx film, the reduction reaction occurs with H in Si3N4 to produce black InO and SnO, Thus, the transmittance of the film is reduced and pixel shading is completed.

Using smartphone cameras and ambient light sensors in distance learning: the attenuation law as experimental determination of gamma correction

In times of the explosion of distance learning, because of emergency due to the pandemic, smartphone sensors and cameras are extremely valuable for teachers as they allow students to perform significant experimental activities in their own homes. The open-source software Tracker can be used in combination with the smartphone camera to perform measurements not only of mechanics activities, but also of optics. In the latter case, it is not always easy for students to understand how the pixel brightness which can be inferred from the taken photos are related to actual physical light intensity. In this paper we present a simple experiment to verify the exponential decay in the intensity of light going through successive sheets of a material (the Lambert law) with two different methods, i.e. using either the smartphone light sensor or the smartphone camera and Tracker. Besides its theoretical significance, the experiment constitutes a useful tool for calibrating the camera/Tracker combination to use it for different experiments.

Albedo and Thermal Ecology of White, Red, and Black Cows (Bos taurus) in a Cold Rangeland Environment.

Simple SummaryThere is a trend of more black hided beef cattle globally, yet cattle on rangelands have limited thermoregulation options. I measured the winter albedo of cows in fresh snow with pixel analysis (n = 3 images) and then external cattle temperatures (Tempcow), and the differences (ΔT) between Tempcow and ambient air temperature (Tempamb) of 638 Tempcow × Tempamb combinations for white (n = 183), red (n = 158), and black (n = 297) Bos taurus females. Cattle were free roaming extensive Wyoming, USA rangelands along a broad thermal gradient (≈−33 °C to +33 °C) from 2016 to 2018. Albedo differed for white, red, and black cows (0.69, 0.16, and 0.04, respectively). Tempcow was explained by Tempamb, clear sky insolation index, and cow albedo. However, ΔT was explained by Tempamb, long-wave infrared radiation, Tempcow, and cow albedo. Tempcow suggests red and black cows experience ~2× higher values than white cows at the coldest temperatures.Cattle in high-elevation rangelands experience cold and hot extremes. Given the increase in black hided cattle globally, thermoregulation options on rangelands, and hide color function affecting mammal thermal ecology, this study quantified winter albedo, external cattle temperatures (Tempcow), and differences (ΔT) between Tempcow and ambient air temperature (Tempamb), for different color cattle along a thermal gradient (≈−33 °C to +33 °C). From 2016 to 2018, I measured 638 individual Tempcow × Tempamb combinations for white (n = 183), red (n = 158), and black (n = 297) Bos taurus female cattle free roaming extensive Wyoming, USA rangelands. Pixel brightness of cow images relative to snow indicated mean (±standard error) albedo for white, red, and black cows (n = 3 of each) was 0.69 (±0.15), 0.16 (±0.04), and 0.04 (±0.01), respectively (p = 0.0027). Tempcow was explained by Tempamb (+), clear sky insolation index (+), and cow albedo (−). However, ΔT was explained by Tempamb (−), long-wave radiation (infrared; RadLW (−)), Tempcow (+), and cow albedo (+). Tempamb relative to ΔT was correlated for all hide colors (all p-values < 0.0001; all r2 values > 0.7)), yet slopes (m) were ~2× greater for red and black cows than white cows.

ANALYSIS OF THE POSSIBILITY OF USING MARKERS EMITTING PULSATING LIGHT IN THE TASK OF LOCALIZATION

This work shows the possibility of using spectral analysis in order to detect characteristic points in recorded images. The specific point is a marker in the form of a diode that flashes at a certain frequency. Main assumptions of the processing algorithm are the recording of a sequence of images and treatment change of level of brightness for each pixel as a time signal. The amplitude spectrum is determined for each time signal. The result of data processing is an amplitude image whose pixels brightness corresponding to the intensity of source of pulsating light emitting specific frequency. This new data representation is used to detect position of markers. The algorithm was re¬searched in order to select optimal marker colors and pulsation frequency. The results are described in a summary.

The impact of inhomogeneous subgrid clumping on cosmic reionization – II. Modelling stochasticity

ABSTRACT Small-scale density fluctuations can significantly affect reionization, but are typically modelled quite crudely. Unresolved fluctuations in numerical simulations and analytical calculations are included using a gas clumping factor, typically assumed to be independent of the local environment. In Paper I, we presented an improved, local density-dependent model for the sub-grid gas clumping. Here, we extend this using an empirical stochastic model based on the results from high-resolution numerical simulations which fully resolve all relevant fluctuations. Our model reproduces well both the mean density-clumping relation and its scatter. We applied our stochastic model, along with the mean clumping one and the Paper I deterministic model, to create large-volume realizations of the clumping field, and used these in radiative transfer simulations of cosmic reionization. Our results show that the simplistic mean clumping model delays reionization compared to local density-dependent models, despite producing fewer recombinations overall. This is due to the very different spatial distribution of clumping, resulting in much higher photoionization rates in the latter cases. The mean clumping model produces smaller H ii regions throughout most of reionization, but those percolate faster at late times. It also causes a significant delay in the 21-cm fluctuations peak and yields lower non-Gaussianity and many fewer bright pixels in the PDF distribution. The stochastic density-dependent model shows relatively minor differences from the deterministic one, mostly concentrated around overlap, where it significantly suppresses the 21-cm fluctuations, and at the bright tail of the 21-cm PDFs, where it produces noticeably more bright pixels.

Defocus-Based Direct Visual Servoing

Direct Visual Servoing (DVS) considers pixel brightness directly as input of robot control. Recent DVS variants consider image processing as smoothing or frequency domain transforms, resulting in large convergence domains. This letter proposes to consider defocus to optically smooth images without processing. The resulting Defocus-based DVS shows convergence domains competing with the state-of-the-art, larger in some challenging cases, for lower complexity.