Shadow Intensity Research Articles

Adaptive Shadow Compensation Method in Hyperspectral Images via Multi-Exposure Fusion and Edge Fusion

Shadows in hyperspectral images lead to reduced spectral intensity and changes in spectral characteristics, significantly hindering analysis and applications. However, current shadow compensation methods face the issue of nonlinear attenuation at different wavelengths and unnatural transitions at the shadow boundary. To address these challenges, we propose a two-stage shadow compensation method based on multi-exposure fusion and edge fusion. Initially, shadow regions are identified through color space conversion and an adaptive threshold. The first stage utilizes multi-exposure, generating a series of exposure images through adaptive exposure coefficients that reflect spatial shadow intensity variations. Fusion weights for exposure images are determined based on exposure, contrast, and spectral variance. Then, the exposure sequence and fusion weights are constructed as Laplacian pyramids and Gaussian pyramids, respectively, to obtain a weighted fused exposure sequence. In the second stage, the previously identified shadow regions are smoothly reintegrated into the original image using edge fusion based on the p-Laplacian operator. To further validate the effectiveness and spectral fidelity of our method, we introduce a new hyperspectral image dataset. Experimental results on the public dataset and proposed dataset demonstrate that our method surpasses other mainstream shadow compensation methods.

Shadow images and observed luminosity of the Bardeen black hole surrounded by different accretions * *Supported by the National Natural Science Foundation of China (11875095, 11903025), the Sichuan Youth Science and Technology Innovation Research Team (21CXTD0038) and Basic Research Project of Science and Technology Committee of Chongqing (cstc2018jcyjA2480)

In this paper, by exploring photon motion in the region near a Bardeen black hole, we studied the shadow and observed properties of the black hole surrounded by various accretion models. We analyzed the changes in shadow imaging and observed luminosity when the relevant physical parameters are changed. For the different spherical accretion backgrounds, we find that the radius of shadow and the position of the photon sphere do not change, but the observed intensity of shadow in the infalling accretion model is significantly lower than that in the static case. We also studied the contribution of the photon rings, lensing rings and direct emission to the total observed flux when the black hole is surrounded by an optically thin disk accretion. Under the different forms of the emission modes, the results show that the observed brightness is mainly determined by direct emission, while the lensing rings will provide a small part of the observed flux, and the flux provided by the photon ring is negligible. By comparing our results with the Schwarzschild spacetime, we find that the existence or change of relevant status parameters will greatly affect the shape and observed intensity of the black hole shadow. These results support the theory that the change of state parameter will affect the spacetime structure, thus affecting the observed features of black hole shadows.

3D cumulus cloud scene modelling and shadow analysis method based on ground-based sky images

Cloud scene modelling and shadow analysis in 3D geographical scenes can provide auxiliary support for evaluating photovoltaic (PV) power generation. Thus far, real cloud scene based on measured data has not been constructed in 3D geographical scenes, and shadow with different intensity caused by cumulus cloud thickness has not been considered. In this study, a 3D cumulus cloud scene modelling and shadow analysis method based on ground-based sky images was proposed. First, a voxel-based 3D cumulus cloud scene modelling on GPU was proposed to model in the 3D geographic space and calculate cumulus cloud density. Then, a cumulus cloud density-based shadow analysis method was proposed, which can express shadow intensity. The experimental result showed that our method can accomplish near real-time 3D cumulus cloud modelling and shadow analysis in a 3D geographic space based on ground-based sky images, and the shadow intensity is inversely proportional to the direct solar radiation.

Food, shadow, and fire influence a tropical bird´s display

Within social signaling contexts, behavioral displays used for territorial defense and courtship may be affected by vegetation characteristics and by human disturbance. The primary aim of this study was to evaluate the relation between motor display variables of the blue-black grassquit (Volatinia jacarina) and vegetation characteristics. Secondly, we tested if human disturbance (fire and grass mowing) could induce variations in display variables. We modelled two display variables involving conspicuousness and energetic motor investment (i.e., leap duration and rate) to examine their relation to habitat characteristics that reflect vegetation complexity (i.e., grass seed abundance, shadow intensity, vegetation density) and evaluated whether confounding factors (e.g., time of day, territory location and breeding status) influenced this relationship. In a second set of analyses, we assessed the influence of fire and grass mowing upon the bird’s display. We found that leap duration increased in contexts of high seed abundance and shadow intensity, and leap rate decreased along the day. Distance from display perches to vegetation patch edge or streets and the presence of an active nest did not predict displays variables. We also show that following a fire event, birds exhibited a lower display rate. Our results indicate that vegetation structure helps to shape the blue-black grassquit display, consistent with the interpretation that courtship exhibitions can signal territory quality. Our findings also show that anthropogenic disturbance can impact a bird’s sexual display and underscores the urgency of further studies about the effects of human activities on animals’ reproductive behaviors. Vegetation characteristics influence resource abundance and provide the backdrop for most animal activities. The degree of vegetation density can either facilitate or confound individuals’ daily activities, since vegetation density influences detection by mates, competitors, and predators. Human-induced habitat changes can influence animal communication by modifying vegetation structure and resource distribution. Our objective was to evaluate the relation between motor display variables of a tropical bird and vegetation characteristics and test if human disturbance could induce variations in display variables. We found that displays are influenced by seed abundance and shadow intensity, leap rate is highest at dawn, and fire reduces display rate. Our results indicate that vegetation structure helps in shaping this species’ sexual display. We highlight the lack of studies evaluating the influence of human activities on animals’ reproductive behaviors.

Power ramp-rates of utility-scale PV systems under passing clouds: Module-level emulation with cloud shadow modeling

The short-term power output variability of solar photovoltaic (PV) systems caused by passing clouds is becoming a major concern for grid operators. As the penetration of utility-scale PV systems boosts, the rapid power fluctuations greatly challenge the grid transient stability. In this regard, the concept of power ramp-rate (RR) has been recently imposed to quantify the PV fluctuations, and a series of ramp regulations are implemented by utilities. However, due to the limitations in terms of high-resolution simulation of utility-scale PV systems and reproducing cloud shadow natures, current studies still show deficiencies in comprehensively investigating the RRs rising from both endogenous and exogenous factors during cloud shadow transitions.With the objective of producing high-resolution and high-accuracy emulations of utility-scale PV systems under passing clouds, thus providing a clearer understanding on the cloud-induced RRs, this paper first sets forth a partial shading emulator that is capable of efficiently mimicking the behaviors of an arbitrary partially shaded PV system, in accuracy of the PV module level. Then a fully customizable shadow model that can reproduce the natures of a real cloud shadow is introduced. Based on the developed emulation tools, the effects of two endogenous factors i.e., PV array arrangement and system orientation, and three exogenous factors i.e., shadow intensity, shadow velocity, and shadow size on RRs are explored for a range of utility-scale PV systems from 1 MW to 60 MW. Furthermore, in order to assess the RRs in reality, a total of 3747 cloud shadow transitions exploited from real measurements have been applied for emulations. The results reveal that the RRs caused by passing clouds are critical problems for system operations, and a larger system can suffer more from ramp violations, indicating that the advanced ramp control strategies should be essential for contemporary utility-scale PV systems.

The potential of Pléiades images with high angle of incidence for reconstructing the coastal cliff face in Normandy (France)

To monitor chalk cliff face along the Normandy coast (NW France) which is prone to erosion, we tested the potential of cliff face 3D reconstruction using pairs of images with high angle of incidence at different dates from the agile Pléiades satellites. The verticality aspect of the cliff face brings difficulties in the 3D reconstruction process. Furthermore, the studied area is challenging mainly because the cliff face is north-oriented (shadow). Pléiades images were acquired over several days (multi-date stereoscopic method) with requested incidence angles until 40°. 3D reconstructions of the cliff face were compared using two software: ASP® and ERDAS IMAGINE®. Our results are twofold. Firstly, despite ASP® provides denser point clouds than ERDAS IMAGINE® (an average of 1.60 points/m² from 40° incidence angle stereoscopic pairs on the whole cliff face of Varengeville-sur-Mer against 0.77 points/m² respectively), ERDAS IMAGINE® provides more reliable point clouds than ASP® (precision assessment on the Varengeville-sur-Mer cliff face of 0.31 m ± 2.53 and 0.39 m ± 4.24 respectively), with a better spatial distribution over the cliff face and a better representation of the cliff face shape. Secondly, the quality of 3D reconstructions depends mostly on the amount of noise from raw images and on the shadow intensity on the cliff face (radiometric quality of images).

An Object-Based Shadow Detection Method for Building Delineation in High-Resolution Satellite Images

In satellite image analysis, detection of shadow plays a critical role in the precise object detection applications. The size and intensity of shadow vary with solar illumination angle and miscellaneous building attributes, which may lead to their misclassification. Hence, there is a need for an accurate and robust shadow detection method. In this paper, an object-based shadow detection method is proposed to extract building shadows and subsequently used to delineate buildings from high-resolution satellite images. In the presented method, a shadow mask is generated at pixel level using a fused ratio map of a visible and a false colour image in HSI colour space. Then, the building shadow map is delineated by an automatic thresholding process on an object level. The results of a qualitative and quantitative analysis reveal the effectiveness and stability of the proposed approach for shadow detection and building delineation in high-resolution satellite images. These satellite images are taken at a different solar illumination angle and for different building attributes. Experimental results show that the proposed method achieves average improvement in F score by 21%, IOU (Intersection over Union) by 16%, and accuracy by 9% as compared to some of the state-of-the-art shadow detection methods.

Ocular Blood Volume Index Based on Scattering Properties of Retinal Vessels Using Spectral Domain Optical Coherence Tomography

ABSTRACTIntroduction: The evaluation of retinal vessels and the retinal blood flow is important for ocular diseases. We introduce a spectral domain optical coherence tomography (SD-OCT) based method for facilitating a retinal blood vessel analysis using the scattering properties of retinal vessels. The intensity of the distal shadow of vessels caused by the scattered signal is measured, correlated with the pulsatile ocular blood flow (POBF), and its repeatability is analyzed.Methods: About 20 eyes of 20 healthy, young participants (mean age 23.15 years, standard deviation 2.3 years) were included in the analysis. Participants underwent ophthalmic diagnostics including three repeated SD-OCT examinations and measurement of POBF. The vessel shadow intensity analysis is based on peripapillary SD-OCT scans and automatically analyses the intensity of the distal vessel shadow compared to its surroundings.Results: The distal shadow of arteries in SD-OCT scans correlated with the POBF (r = 0.647, p = 0.002). Furthermore, the shadow intensity correlated with the established morphological arterio-venous ratio. The evaluation of repeatability was performed using the interclass correlation coefficient (ICC), showing good repeatability for individual vessels (ICC = 0.825) and arteries (ICC = 0.820).Conclusions: In summary, we indicate that the scattering properties of retinal vessels in SD-OCT images might correlate with the vessel morphology and for retinal arteries with the retinal blood flow volume as well. Further studies are needed to establish this method’s sensitivity and specificity in participants with retinal and cardiovascular diseases.

Optical Coherence Tomography-Based Scattering Properties of Retinal Vessels in Glaucoma Patients

ABSTRACTPurpose: Clinical trials have demonstrated that retinal blood flow deficiencies are present in patients with open-angle glaucoma (OAG). We introduce a method for facilitating retinal vessel analysis: The intensity of the distal shadow of vessels in optical coherence tomography (OCT) caused by the scattered signal is analyzed, compared between healthy subjects and OAG patients and correlated with OCT angiography (OCT-A) flow density.Patients and Methods: We recruited 80 patients with diagnosed OAG (mean age 63.4 ± 13.2 years) and 80 healthy age-matched control subjects for comparison, and 20 patients for the correlation with OCT-A flow density. Patients received perimetry, peripapillary OCT measurements, and selected patients OCT-A of the papillary area. The vessel shadow intensity (VSI) is based on peripapillary OCT scans: the intensity of the distal vessel shadow was automatically compared to its surroundings, separated by arteries and veins. Flow density of the OCT-A scan was calculated by binarization and quantification of the pixel density.Results: The VSI for arteries was in OAG patients with 7.52 ± 2.62 [%] significantly lower compared to healthy subjects (9.03 ± 3.38 [%], p = 0.0029). In veins, the VSI was as well significantly lower for OAG patients (14.9 ± 3.59 [%]) compared to healthy subjects (17.46 ± 4.45 [%], p < 0.0001). Furthermore, in OAG patients there was a significant correlation of mean deviation of the visual field results with the veins’ VSI (p = 0.0006; r = −0,454). There was no significant correlation of scattering properties with OCT-A flow density (p > 0.05).Conclusions: We conclude that the OCT-based analysis of the scattering properties of retinal vessels differs significantly between patients with OAG and healthy subjects. Furthermore, changes in the scattering properties of veins correlated with the stage of the disease in terms of visual field deficits. These properties might complement existing measurements of ocular blood flow including OCT-A flow density.

Multifeature fusion for automatic building change detection in wide-area imagery

A strategy for detecting changes in known building regions in multitemporal visible and near-infrared imagery based on a linear combination of independent features is presented. Features identified for building and background detection include vegetation, texture, shadow intensity, and distance from known road areas. The resulting building candidates are classified by shape using a unique difference of Gaussian technique. Building regions reported in the reference dataset that indicate the initial observation time are revisited to check for changes in building candidates not identified in the feature fusion strategy. The performance of the proposed technique is tested on real-world aerial imagery and is evaluated visually and quantitatively. Compared with the gradient and normalized difference vegetation index-based building detection methods, the proposed fusion methodology yields better results. For building detection, it provided a completeness result of an average 82.08% and building change detection completeness result of an average 85.67% in our evaluations with five sample images, which included rural, suburban, and urban areas.

点光源による半影表現のためのレイトレーシング拡張アルゴリズム

Penumbra is an important factor for three dimensional Computer Graphics in order to represent realistic images especially at interior views. Point light represents images with sharp-edge shadow that is far from reality. On the other hand, area light casts penumbra at the situation where occluders prevent some part of light area from reaching calculation points. Although path tracing and radiosity are technologies that handle area light, both of them take so enormous times for processing that they are not suitable to use at the stage of reviewing designs which are weighed with turnaround time. Therefore, this paper proposes a new high-speed algorithm that represents high resolution penumbra casted from psuedo area light by applying ray tracing that handles point light only. It is inevitable that the previous technologies, namely percentage closer filtering (PCF) and variance shadow maps (VSM), generate low quality penumbra because they are algorithms based on shadow maps that include aliasing problem. We name this new algorithm “light obstacle depth”. Light obstacle depth calculates intensity of shadow by point light at each calculation point at first and subsequently blends shadow around the calculation point according to the distance between the nearest occluder and the point. Ray tracing produces shadow with shading at a time which contains textures, reflection, transparency, and refraction, etc. However, light obstacle depth separates shadow calculation process from other shading process, calculates shadow intensity independently, stores them at each pixel to make shadow buffer, and at last combines the shadow buffer and other shading together after blending shadow buffer. Blending problems around occluders occur when we apply the basic blending technique, so we propose an enhanced blending technique to solve the problem. In addition, we show the equation that estimates blending area using size, direction, and distance of an area light simulated. We also propose a technique to estimate blending area on image with perspective transformation. To validate quality and speed of the new algorithm, we used two different types of models, namely a model with scattered polygons and a model crowded in small area. Compared with images generated accurately by area light, images by our new algorithm show that light obstacle depth is able to simulate penumbra of area light with practically sufficient quality. In terms of the calculation time, our new algorithm is capable to generate penumbra at almost the same time as point light calculation and several tens of times faster than normal area light calculation. Furthermore, we show that calculation speed of our new algorithm becomes more efficient for more complex data. We aim that light obstacle depth is processed using GPGPU (general purpose GPU) technology. As GPGPU processing is expected to be several tens of times acceleration, real time penumbra generation will come true after GPGPU application to light obstacle depth is realized.

Estimating Illumination Distribution to Generate Realistic Shadows in Augmented Reality

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.

Protocol for acclimatization of in vitro cultured Potamogeton praelongus – aspect of plantlet size and type of substrate

&lt;p&gt;The aim of the experiment was to determine suitable substrate type and optimal plant size for transfer of plantlets from in vitro to ex vitro under experimental outdoor conditions. Tests focused on the effect of substrate type (muddy and sandy) and starting size of plantlets gained through in vitro seed germination (0–3, 3.1–5,5.1–6, 6.1–10 cm) on plant growth. Three parameters (fresh weight, length, and the number of leaves) were compared to evaluate growth. Basic water parameters in experimental water tanks were regularly measured (pH, temperature, electrical conductivity, shadow intensity) and controlled to reach similar conditions to those in the natural habitat of this species. Overwintering was studied in a cellar with newly defined size categories (≤6, 6.1–8, 8.1–10, 10.1–12, 12.1–15 cm).&lt;/p&gt;&lt;p&gt;Both substrate type and starting size of plantlets significantly impacted growth. Plantlets grew better in the muddy substrate while a 100% success rate of rooting was gained with a starting size of 6.1–10 cm in both substrates. The biggest increase in fresh weight was observed with a starting size of 3.1–5 cm and 5.1–6 cm in both substrates. The greatest increase in fresh weight was observed in plants with a starting size of 3.1–5 cm in the muddy substrate (more than 95% increase). The best overwintering results were gained in the 6.1–8 cm size category.&lt;/p&gt;

Human Body Tracking and Pose Estimation Using Modified Camshift Algorithm

In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMShift Algorithm we propose searches the skin color region by detecting the skin color area from background model. Kalman filter stabilizes the floated search area of CAMShift Algorithm. Each occlusion areas are avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed modified Camshaft algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

칼만 필터와 가중탐색영역 CAMShift를 이용한 휴먼 바디 트래킹 및 자세추정

본 논문에서는 사람의 신체 일부분을 추적하는 시스템을 위해서 피부영역을 추출하고 여러 개의 영역을 추적하는 칼만 필터와 가중 탐색 영역을 이용한 다중 CAMShift 알고리즘(KWMCAMShift)을 제안한다. 배경모델을 구성하고 손과 얼굴의 피부색영역을 탐색 영역으로 하는 CAMShift를 제안한다. 이때 CAMShift의 유동적인 탐색영역을 안정화하기 위해 칼만 필터를 이용한다. 손과 얼굴 등이 상호 겹쳐지는 경우 탐색영역의 손실을 막기 위해 주 탐색영역과 비 탐색영역에 대한 가중치를 부가하여 서로 폐색 영역에 대한 회피 알고리즘을 제안한다. 얼굴 영역과 양손의 영역을 중심으로 인간의 자세를 추정하여 어깨와 손과의 관계로 팔꿈치를 추정하였고, 가우시안 배경 모델에 생성되는 그림자를 제거하여 발끝을 찾아 신체 전체를 추정하였다. 제안된 KWMCAMShift 알고리즘을 적용하였을 때 폐색 시에도 96.82%의 인식률을 보였으며 실시간이 가능하였다. In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

Shadows: Young Taiwanese children’s views and understanding

The purpose of this study was to examine young children’s views about shadows. Young children hear references to or are involved in many scientific experiences in their everyday lives, and shadows are a part of children’s everyday experiences. Young children may have constructed their knowledge about shadows through their daily experiences. Therefore, a total of 32 children, of which one‐half were four years old and one‐half were five years old, were individually interviewed twice to elicit their views and understanding of shadows. Data were collected by a mixture of picture‐pointing, verbal explanation, and manipulation, and were analysed both quantitatively and qualitatively. We focused on five facets of children’s ideas about shadows: ideas about the source of light, shadow orientation, shadow shape, shadow size, and shadow intensity. The five year olds performed significantly better on production of shadows, production of shadow shape, and production of shadow size, and also gave more reasonable explanations for their choices than did the four year olds, showing a better understanding of the concept of shadows. Another significant finding of the study was that young children have a much more sophisticated understanding of shadows than Piaget originally suggested and than their verbal explanations imply.

The Shadow Meets the Mask: Pyramid‐Based Shadow Removal

AbstractIn this paper we propose a novel method for detecting and removing shadows from a single image thereby obtaining a high‐quality shadow‐free image. With minimal user assistance, we first identify shadowed and lit areas on the same surface in the scene using an illumination‐invariant distance measure. These areas are used to estimate the parameters of an affine shadow formation model. A novel pyramid‐based restoration process is then applied to produce a shadow‐free image, while avoiding loss of texture contrast and introduction of noise. Unlike previous approaches, we account for varying shadow intensity inside the shadowed region by processing it from the interior towards the boundaries. Finally, to ensure a seamless transition between the original and the recovered regions we apply image inpainting along a thin border. We demonstrate that our approach produces results that are in most cases superior in quality to those of previous shadow removal methods. We also show that it is possible to easily composite the extracted shadow onto a new background or modify its size and direction in the original image.

On the refracted patterns produced by liquid vortices

A theoretical analysis of the refracted shadows produced by steady and time-decaying liquid vortices under uniform illumination from above is given in this article. An expression for the induced shadow intensity is derived and found to be a function of the vortex’s free surface profile, i.e., function of the static pressure distribution. The patterns for different focusing depth are given and compared with previous visualization results from the literature. The phenomenon is examined and illustrated as a bench mark case by using both steady and time-decaying algebraic vortex models. However, this study can be extended to check the feasibility of recovering the main flow properties by analyzing the luminous image intensity of the refracted patterns. The present analysis is valid only when the swirl velocity is order of magnitude higher than the meridional flow components and the vorticity is concentrated within the core region and of intense conditions.

Shadow Segmentation and Classification in a Constrained Environment

A shadow identification and classification method for real images is developed in this paper. The method is based on the extensive analysis of shadow intensity and shadow geometry in an environment with simple objects and a single area light source. The procedure for identifying shadows is divided into three processes: low level, middle level, and high level. The low level process extracts dark regions from images. Dark regions contain both shadows and surfaces with low reflectance. The middle level process performs feature analysis on dark regions, including detecting vertices on the outlines of dark regions, identifying penumbrae in dark regions. classifying the subregions in dark regions as self-shadows or cast shadows, and finding object regions adjacent to dark regions. The high level process integrates the infonnation derived from the previous processes and confirms shadows among the dark regions.

Impression of total solar eclipse in TIROS-N AVHRR Imagery

The National Remote Sensing Agency Landsat Earth Station near Hyderabad, India, had a unique opportunity to track the TIROS-N 10:00:28-10:15:53 GMT pass which very nearly coincided with the path of the 16 February 1980 total solar eclipse. The enhanced pictures produced, using data in visible and near-IR bands, very clearly show the eclipse shadow zones. Using data on the solar eclipse, the authors have attempted an explanation of the observed variations in shadow intensity within a zone and between different zones in the enhanced picture in the visible band. An explanation of the observed shadow geometry has also been attempted. To make the data useful for further studies, approximate computed values of scan time, latitude, and longitude coordinates for shadow boundary discriminating points have also been presented.