Illumination Map Research Articles

MarsLux: HI‐Resolution Illumination Maps Generator for Mars

AbstractIllumination simulation codes for the Moon's surface have been thoroughly developed during the last years. Despite works done for the Moon, no studies have investigated the relation between sunlight illumination and the Martian surface applying those codes done for the Moon to Mars. The objective of this work is to describe the development of a surface illumination simulation code, called MarsLux, which allows users to make a detailed investigation of the illumination conditions on Mars, based on its topography and the relative position of the Sun. Our code can derive accurate illumination maps, form topographic data, showing areas that are fully illuminated, areas in total shadow, and areas with partial shade, in short computational times. Although the code does not take into account any atmospheric effect, the results proved to be of high accuracy. The maps generated are useful for geomorphological studies, to study gullies, thermal weathering, or mass wasting processes as well as for producing energy budget maps for future exploration missions.

Nighttime Single Image Dehazing via Pixel-Wise Alpha Blending

In this paper, we propose a novel method to address the nighttime single image dehazing problem. Estimation of the ambient illumination map and transmission map are the key steps of modern dehazing approaches. For hazy scenes at night, ambient illumination is usually not globally isotropic as a nighttime scene typically contains multiple light sources. Frequently, Light source regions and non-light source regions exhibit distinct color features. However, existing nighttime dehazing methods have been attempting to process these two regions based on identical prior assumptions. Moreover, the commonly-used local maximum pixel method tends to over-estimate the ambient illumination. These two drawbacks result in color distortions and halo artifacts around the light source regions in the output images. In this work, we present a pixel-wise alpha blending method for estimating the transmission map, where the transmissions estimated from dark channel prior (non-light source region) and the proposed bright channel prior (light source region) are effectively blended into one transmission map guided by a brightness-aware weights map. Based on the Retinex theory, a channel difference guided filtering method is proposed to estimate the ambient illumination, which produces a spatially variant low-frequency passband that selectively retains the high-frequency edge details. Extensive experiments on the benchmarks demonstrate that our method outperforms the state-of-the-art methods for nighttime image dehazing, especially in terms of color consistency and halo artifacts reduction in the dehazed images.

Obtaining reliable source locations with time reverse imaging: limits to array design, velocity models and signal-to-noise ratios

Abstract. Time reverse imaging (TRI) is evolving into a standard technique for locating and characterising seismic events. In recent years, TRI has been employed for a wide range of applications from the lab scale, to the field scale and up to the global scale. No identification of events or their onset times is necessary when locating events with TRI; therefore, it is especially suited for locating quasi-simultaneous events and events with a low signal-to-noise ratio. However, in contrast to more regularly applied localisation methods, the prerequisites for applying TRI are not sufficiently known.To investigate the significance of station distributions, complex velocity models and signal-to-noise ratios with respect to location accuracy, numerous simulations were performed using a finite difference code to propagate elastic waves through three-dimensional models. Synthetic seismograms were reversed in time and reinserted into the model. The time-reversed wave field back propagates through the model and, in theory, focuses at the source location. This focusing was visualised using imaging conditions. Additionally, artificial focusing spots were removed using an illumination map specific to the set-up. Successful locations were sorted into four categories depending on their reliability. Consequently, individual simulation set-ups could be evaluated by their ability to produce reliable source locations.Optimal inter-station distances, minimum apertures, relations between the array and source locations, heterogeneities of inter-station distances and the total number of stations were investigated for different source depths and source types. Additionally, the accuracy of the locations was analysed when using a complex velocity model or a low signal-to-noise ratio.Finally, an array in southern California was investigated regarding its ability to locate seismic events at specific target depths while using the actual velocity model for that region. In addition, the success rate with recorded data was estimated.Knowledge about the prerequisites for using TRI enables the estimation of success rates for a given problem. Furthermore, it reduces the time needed to adjust stations to achieve more reliable locations and provides a foundation for designing arrays for applying TRI.

Evidence of Extensive Ice Deposits Near Mercury’s South Pole

New radar observations and refined illumination maps reveal uneven water ice deposits twice the size of those found around the planet’s north pole, suggesting the source may be a recent comet impact.

Improving fault image by determination of optimum seismic survey parameters using ray-based modeling

In complex structures such as faults, salt domes and reefs, specifying the survey parameters is more challenging and critical owing to the complicated wave field behavior involved in such structures. In the petroleum industry, detecting faults has become crucial for reservoir potential where faults can act as traps for hydrocarbon. In this regard, seismic survey modeling is employed to construct a model close to the real structure, and obtain very realistic synthetic seismic data. Seismic modeling software, the velocity model and parameters pre-determined by conventional methods enable a seismic survey designer to run a shot-by-shot virtual survey operation. A reliable velocity model of structures can be constructed by integrating the 2D seismic data, geological reports and the well information. The effects of various survey designs can be investigated by the analysis of illumination maps and flower plots. Also, seismic processing of the synthetic data output can describe the target image using different survey parameters. Therefore, seismic modeling is one of the most economical ways to establish and test the optimum acquisition parameters to obtain the best image when dealing with complex geological structures. The primary objective of this study is to design a proper 3D seismic survey orientation to achieve fault zone structures through ray-tracing seismic modeling. The results prove that a seismic survey designer can enhance the image of fault planes in a seismic section by utilizing the proposed modeling and processing approach.

LightenNet: A Convolutional Neural Network for weakly illuminated image enhancement

Weak illumination or low light image enhancement as pre-processing is needed in many computer vision tasks. Existing methods show limitations when they are used to enhance weakly illuminated images, especially for the images captured under diverse illumination circumstances. In this letter, we propose a trainable Convolutional Neural Network (CNN) for weakly illuminated image enhancement, namely LightenNet, which takes a weakly illuminated image as input and outputs its illumination map that is subsequently used to obtain the enhanced image based on Retinex model. The proposed method produces visually pleasing results without over or under-enhanced regions. Qualitative and quantitative comparisons are conducted to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed method achieves superior performance than existing methods. Additionally, we propose a new weakly illuminated image synthesis approach, which can be use as a guide for weakly illuminated image enhancement networks training and full-reference image quality assessment.

Evaluating color and texture features for forgery localization from illuminant maps

Images are widely accepted as a record of events even when images are prone to easy manipulations. It is difficult to identify image alterations by the human visual system. Once an image is identified as forged, the next step is to locate forged regions. Recently, distribution of scene illumination across an image has been analyzed to detect forged images and to locate forged image regions. In this paper, we investigate the problem of locating spliced image region based on illumination inconsistency. We investigated the discriminative power of a number of color and texture descriptors in locating spliced image regions. During digital crime investigations, often it is required to detect the spliced face in a group photo. Here, we have selected forged images containing human facial regions where the regions to be compared are of similar object material, human skin regions. We evaluated various color, texture, and combined color-texture descriptors in an unsupervised manner by comparing the distance between the feature vectors to identify the inconsistent image region. We also investigated the performance of different histogram similarity measures including heuristic histogram distance measures, non-parametric test statistics, information theoretic divergences, and cross-bin measures. Experiments show that the Local Phase Quantization (LPQ) descriptor performs best in identifying the spliced image region from the illuminant map.

Low-light image enhancement with a refined illumination map

It has become very popular to take photographs in everyone’s daily life. However, the visual quality of a photograph is not always guaranteed due to various factors. One common factor is the low-light imaging condition, which conceals visual information and degenerates the quality of a photograph. It is preferable for a low-light image enhancement model to complete the following tasks: improving contrast, preserving details, and keeping robust to noise. To this end, we propose a simple but effective enhancing model based on the simplified Retinex theory, of which the key is to estimate a good illumination map. In our model, we apply an iterative self-guided filter to refine the initial estimation of an illumination map, making it aware of local structure of image contents. In experiments, we validate the effectiveness of our method in various aspects, and compare our model with several state-of-the-art ones. The results show that our method effectively adjusts the global image contrast, recovers the concealed details and keeps the robustness against noise.

Analysis of a Moon outpost for Mars enabling technologies through a Virtual Reality environment

The Moon is now being considered as the starting point for human exploration of the Solar System beyond low-Earth orbit. Many national space agencies are actively advocating to build up a lunar surface habitat capability starting from 2030 or earlier: according to ESA Technology Roadmaps for Exploration this should be the result of a broad international cooperation. Taking into account an incremental approach to reduce risks and costs of space missions, a lunar outpost can be considered as a test bed towards Mars, allowing to validate enabling technologies, such as water processing, waste management, power generation and storage, automation, robotics and human factors. Our natural satellite is rich in resources that could be used to pursue such a goal through a necessary assessment of ISRU techniques.The aim of this research is the analysis of a Moon outpost dedicated to the validation of enabling technologies for human space exploration.The main building blocks of the outpost are identified and feasible evolutionary scenarios are depicted, to highlight the incremental steps to build up the outpost. Main aspects that are dealt with include outpost location and architecture, as well as ISRU facilities, which in a far term future can help reduce the mass at launch, by producing hydrogen and oxygen for consumables, ECLSS, and propellant for Earth-Moon sorties and Mars journeys. A test outpost is implemented in a Virtual Reality (VR) environment as a first proof-of-concepts, where the elements are computer-based mock-ups. The VR facility has a first-person interactive perspective, allowing for specific in-depth analyses of ergonomics and operations. The feedbacks of these analyses are crucial to highlight requirements that might otherwise be overlooked, while their general outputs are fundamental to write down procedures. Moreover, the mimic of astronauts' EVAs is useful for pre-flight training, but can also represent an additional tool for failures troubleshooting during the flight controllers' nominal operations. Additionally, illumination maps have been obtained to study the light conditions, which are essential parameters to assess the base elements location. This unique simulation environment may offer the largest suite of benefits during the design and development phase, as it allows to design future systems to optimize operations, thus maximizing the mission's scientific return, and to enhance the astronauts training, by saving time and cost.The paper describes how a virtual environment could help to design a Moon outpost for an incremental architecture strategy towards Mars missions.

An efficient mulithreading algorithm for the simulation of global illumination

The calculation of global illumination taking into account not only the direct light but also all its possible reflections is an important part of the synthesis of realistic images. The simulation of global illumination requires a lot of computational resources. The performance of modern computers directly depends on the number of cores, which allow one to use tens of parallel computation threads. The paper is devoted to the effective use of multicore computers for simulating the global illumination. The computation results are represented in a uniform illumination map. The proposed algorithm dynamically creates additional threads for the critical branches of the computation process or processing of results. As a result, the uniform load of computation threads as achieved, and the physical and virtual cores are fully loaded.

Study of a full-wave equation-based seismic illumination analysis

Recently, the seismic illumination analysis has progressed considerably in methodology which has been developed not only from one-way wave equation-based illumination to full-wave equation-based illumination but also from conventional illumination analysis to directional illumination analysis with local plane-wave decomposition. Because of the inherent defects of the one-way wave equation, the full-wave equation-based seismic illumination methods have increasingly attracted more attention. However, full-wave equation-based wavefield includes both downgoing and upgoing waves, such as transmissive, turning, and reflected waves. This hybrid wavefield can mislead us in seismic illumination analysis. For the sake of a preferable seismic illumination analysis method, we separated upgoing and downgoing wavefields in the time domain using Poynting vector and defined the incident and reflected illumination analysis functions based on the separated wavefields. Furthermore, we applied these two new illumination functions in seismic illumination analysis with the Sigsbee2a model. Multiple-shot illumination results show that the full-wave illumination and incident illumination maps are consistent with the seismic migration image. Because of no interference caused by the interactions between upgoing and downgoing waves, the incident illumination is superior for illumination analysis. Successful application of the full-wave equation-based incident and reflected illumination functions in the actual acquisition direction design of marine seismic geometry verifies their applicability and reveals their excellent prospects.

A novel Retinex image enhancement approach via brightness channel prior and change of detail prior

In this paper, we propose a novel Retinex image enhancement approach by adopting two important prior named brightness channel prior (BCP) and change of detail (CoD) prior. We first derive a rough illumination map estimation method via BCP and Retinex model. Then, we present a combination refining method which involves the guided filter and a new total variation (TV) smoothing operator to eliminate the block effect in the rough illumination map while maintain the local smoothness property. In addition, we propose a novel sharping algorithm rely on CoD prior to improve the visual effect of the degraded image. Experimental results verify that our approach outperforms current approaches in terms of effectiveness, efficiency and universality.

Lighting Equilibrium Distribution Maps and Their Application to Face Recognition Under Difficult Lighting Conditions

In this paper, a novel facial-patch based recognition framework is proposed to deal with the problem of face recognition (FR) on the serious illumination condition. First, a novel lighting equilibrium distribution maps (LEDM) for illumination normalization is proposed. In LEDM, an image is analyzed in logarithm domain with wavelet transform, and the approximation coefficients of the image are mapped according to a reference-illumination map in order to normalize the distribution of illumination energy due to different lighting effects. Meanwhile, the detail coefficients are enhanced to achieve detail information emphasis. The LEDM is obtained by blurring the distances between the test image and the reference illumination map in the logarithm domain, which may express the entire distribution of illumination variations. Then, a facial-patch based framework and a credit degree based facial patches synthesizing algorithm are proposed. Each normalized face images is divided into several stacked patches. And, all patches are individually classified, then each patch from the test image casts a vote toward the parent image classification. A novel credit degree map is established based on the LEDM, which is deciding a credit degree for each facial patch. The main idea of credit degree map construction is the over-and under-illuminated regions should be assigned lower credit degree than well-illuminated regions. Finally, results are obtained by the credit degree based facial patches synthesizing. The proposed method provides state-of-the-art performance on three data sets that are widely used for testing FR under different illumination conditions: Extended Yale-B, CAS-PEAL-R1, and CMUPIE. Experimental results show that our FR frame outperforms several existing illumination compensation methods.

LIME: Low-Light Image Enhancement via Illumination Map Estimation.

When one captures images in low-light conditions, the images often suffer from low visibility. Besides degrading the visual aesthetics of images, this poor quality may also significantly degenerate the performance of many computer vision and multimedia algorithms that are primarily designed for high-quality inputs. In this paper, we propose a simple yet effective low-light image enhancement (LIME) method. More concretely, the illumination of each pixel is first estimated individually by finding the maximum value in R, G, and B channels. Furthermore, we refine the initial illumination map by imposing a structure prior on it, as the final illumination map. Having the well-constructed illumination map, the enhancement can be achieved accordingly. Experiments on a number of challenging low-light images are present to reveal the efficacy of our LIME and show its superiority over several state-of-the-arts in terms of enhancement quality and efficiency.

Illuminant-Based Transformed Spaces for Image Forensics

In this paper, we explore transformed spaces, represented by image illuminant maps, to propose a methodology for selecting complementary forms of characterizing visual properties for an effective and automated detection of image forgeries. We combine statistical telltales provided by different image descriptors that explore color, shape, and texture features. We focus on detecting image forgeries containing people and present a method for locating the forgery, specifically, the face of a person in an image. Experiments performed on three different open-access data sets show the potential of the proposed method for pinpointing image forgeries containing people. In the two first data sets (DSO-1 and DSI-1), the proposed method achieved a classification accuracy of 94% and 84%, respectively, a remarkable improvement when compared with the state-of-the-art methods. Finally, when evaluating the third data set comprising questioned images downloaded from the Internet, we also present a detailed analysis of target images.

On Counting Metamers.

Objects reflecting lights, which invoke the identical responses of the photoreceptors, are called metameric. Metameric objects match each other in color. Assuming all the reflecting objects equiprobable, the probability density distribution on the set of all the classes of mutually metameric objects is evaluated. Metamerism depends on illumination. Objects metameric under one illumination might produce different photoreceptor responses (i.e., mismatch each other) under the other illumination. In particular, objects mapping to a single point in the photoreceptor response space under one illumination map to a volume (referred to as the metamer mismatch volume) in the photoreceptor response space under the second illumination. The probability density distribution in the metamer mismatch volume is also evaluated. Its center is expressed as a function of the photoreceptor spectral sensitivities and the spectral power distributions of the illuminants. Potential application of the obtained results to color management is discussed.

Spatial-contextual texture and edge analysis approach for unsupervised change detection of faces in counterfeit images

Images transfer more information about expressing an occasion than words. The skillful knowledge should exist to perceive the change in objects present in those images. Also, there is no sign existing to crisscross the objects are liable or not. The internet images should be legitimate to approve its truthiness. The cloned image forgery can be performed by many sophisticated cameras and by editing software. Therefore, a proposal should present to detect the change in counterfeit or forgery-based images to warrant the objects existing in the image are true. The input images are pre-processed to generate the Gray world and illuminant maps. The faces in the input images are segmented using both automatic and semi-automatic methods. The texture from the faces is bred using the values from pixels of locality. Canny detector is applied to distinguish the edge in the face. The features acquired from the faces are compared with each other to sense the counterfeit face that is spliced in the original image to make them as the composite image. The features are then trained to catalog them as forgery or no forgery. Existing methodologies has the capability to identify forgery in image with the extreme of two faces. The proposed method has the prospect to spot every faces present in the image. The cloned counterfeit faces are removed from the image by spatial contextual correlation strategy of image completion. Experimental results show that the proposed methodology achieves well than the other approaches present in the literature.

Shadow Detection by Local Color Constancy

This paper describe the technique of shadow detection properly, this technique can detect both the cast and selfshadow. The method exploits local color constancy properties which are cause of reflectance suppression in excess of shadowed regions. For detecting shadowed areas in a scene, the values of the backdrop image are separated by values of the current frame in the true color (RGB) space. We use all three type of colour space in our work. Illumination map is extracted using a steerable filter framework based on global, local correlations in low and high frequency bands respectively. The lighting and colour features so extracted are then input to a decision trees are designed to detect shadow edges using AdaBoost. The simulation results give us an idea about the performance of the proposed method as good with boundary marking on shadow and nonshadow region with high accuracy.

Lighting system design based on a sensor network for energy savings in large industrial buildings

This paper presents a new method based on a sensor network for designing a lighting control system for an industrial building. An illumination mapping between the work plane and the horizontal plane was derived for sensor placement to generate rules for sensor layout. Online sensor data sampling and a control center database with a real-time update algorithm were applied to lessen the effects of interference and luminous decay. We implemented the method for the lighting system of an industrial building in Xi’an, China. Skylights combined with artificial lighting were designed for daytime lighting. The optimized placement and a scene-control strategy for the artificial lighting system were generated by simulations with DIALux and Autodesk Ecotect Analysis. Daily lighting consumption data for August, 2014, demonstrated that the control system strategy realized lighting energy savings of up to an average of 80% on cloudy days. The design can be used as a reference for new industrial construction or retrofit applications.

Illumination Map in Hokuriku District(<Feature>Let's Keep and Refine the Light on Our Tradition for the Bright Future! - Hokuriku Branch)

This is a map where introduce the locations to enjoy illumination such as lighting-up spots, nice night views, and illumination events in Hokuriku District. If you access using the QR codes on the map, you can get the details of information about the location from the special site. Please enjoy it!