Adaptive Shadow Detection Using a Blackbody Radiator Model

Makarau, Aliaksei; Richter, R.; Müller, Rupert; Reinartz, Peter

doi:10.1109/tgrs.2010.2096515

Cited by 69 publications

(25 citation statements)

References 19 publications

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“…The fuzzy-classification based on derived top-of-atmopsphere (TOA) ortho images is described in Krauß et al (2012). An additional method used here is the shadow detection shown by Makarau et al (2011). The basic approach for change detection used in this work is the robust change detection method described in Tian and Reinartz (2011) and Tian et al (2014).…”

Section: Preliminary Workmentioning

confidence: 99%

“…For this the multispectral imagery is converted first to a top of atmosphere (TOA) reflectances image Itoa. Afterwards a shadow mask ms is calculated following Makarau et al (2011) using the blue, green and red channel of Itoa. Applying the spectral fuzzy classification method described in Krauß et al (2012) to Itoa allows the extraction of land cover probability maps.…”

Section: Dsm Correction and Ortho Projectionmentioning

confidence: 99%

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3D-information fusion from very high resolution satellite sensors

Krauss

d’Angelo

Kuschk

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pléiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

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Section: Preliminary Workmentioning

confidence: 99%

Section: Dsm Correction and Ortho Projectionmentioning

confidence: 99%

3D-information fusion from very high resolution satellite sensors

Krauss

d’Angelo

Kuschk

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…The current methods for shadow detection can be divided into three types [11][12][13]: (1) property-based methods [9,[13][14][15][16][17][18][19][20]; (2) geometrical methods [14,[17][18][19][20]; and (3) machine learning methods [15,16,21,22].…”

Section: Introductionmentioning

confidence: 99%

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

Wang

Yuan

et al. 2017

Remote Sensing

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Abstract:The application potential of very high resolution (VHR) remote sensing imagery has been boosted by recent developments in the data acquisition and processing ability of aerial photogrammetry. However, shadows in images contribute to problems such as incomplete spectral information, lower intensity brightness, and fuzzy boundaries, which seriously affect the efficiency of the image interpretation. In this paper, to address these issues, a simple and automatic method of shadow detection is presented. The proposed method combines the advantages of the property-based and geometric-based methods to automatically detect the shadowed areas in VHR imagery. A geometric model of the scene and the solar position are used to delineate the shadowed and non-shadowed areas in the VHR image. A matting method is then applied to the image to refine the shadow mask. Different types of shadowed aerial orthoimages were used to verify the effectiveness of the proposed shadow detection method, and the results were compared with the results obtained by two state-of-the-art methods. The overall accuracy of the proposed method on the three tests was around 90%, confirming the effectiveness and robustness of the new method for detecting fine shadows, without any human input. The proposed method also performs better in detecting shadows in areas with water than the other two methods.

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“…Under these conditions, target objects in a shadow area are irradiated by the scattered light and reflected light from the surrounding environment (Chakraborti, 2007;Makarau et al, 2011;Adeline et al, 2013;Wu et al, 2014). Conversely, target objects in a non-shadow area not only receive scattered and reflected light, but also direct light.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Spectral Characteristics of Shadow Area From Ads-40 High Radiometric Resolution Aerial Images

Hsieh

Chen

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VII, WG VII/4KEY WORDS: Shadow, shadow spectra, ADS-40, high radiometric resolution ABSTRACT:The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i) The DN values in shadow area are much lower than in nonshadow area; (ii) DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii) The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv) The shadow area NIR of vegetation category also shows a strong reflection; (v) Generally, vegetation indexes (NDVI) still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40) is potential for the extract land cover information of shadow areas.

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Adaptive Shadow Detection Using a Blackbody Radiator Model

Cited by 69 publications

References 19 publications

3D-information fusion from very high resolution satellite sensors

3D-information fusion from very high resolution satellite sensors

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

Analyzing Spectral Characteristics of Shadow Area From Ads-40 High Radiometric Resolution Aerial Images

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