A Review on Various Shadow Detection and Compensation Techniques in Remote Sensing Images

Mostafa, Yasser G.

doi:10.1080/07038992.2017.1384310

Cited by 51 publications

(29 citation statements)

References 93 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Applying an NIR or red edge spectral band as master or sole camera when studying canopy structure or change detection in orthomosaic products of complex canopies appears to improve reconstruction of target features. Low solar elevations are typically avoided in remote sensing, with solar noon targeted to reduce shadow and improve radiometry (e.g., [57,58]). It has been previously demonstrated at lower spatial resolutions that reconstruction is possible at low solar elevations for large-format digital imagery [59].…”

Section: Treesmentioning

confidence: 99%

Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models

Fletcher

Mather

2020

Remote Sensing

View full text Add to dashboard Cite

Small uncrewed aerial systems (UASs) generate imagery that can provide detailed information regarding condition and change if the products are reproducible through time. Densified point clouds form the basic information for digital surface models and orthorectified mosaics, so variable dense point reconstruction will introduce uncertainty. Eucalyptus trees typically have sparse and discontinuous canopies with pendulous leaves that present a difficult target for photogrammetry software. We examine how spectral band, season, solar azimuth, elevation, and some processing settings impact completeness and reproducibility of dense point clouds for shrub swamp and Eucalyptus forest canopy. At the study site near solar noon, selecting near infrared camera increased projected tree canopy fourfold, and dense point features more than 2 m above ground were increased sixfold compared to red spectral bands. Near infrared (NIR) imagery improved projected and total dense features two- and threefold, respectively, compared to default green band imagery. The lowest solar elevation captured (25°) consistently improved canopy feature reconstruction in all spectral bands. Although low solar elevations are typically avoided for radiometric reasons, we demonstrate that these conditions improve the detection and reconstruction of complex tree canopy features in natural Eucalyptus forests. Combining imagery sets captured at different solar elevations improved the reproducibility of dense point clouds between seasons. Total dense point cloud features reconstructed were increased by almost 10 million points (20%) when imagery used was NIR combining solar noon and low solar elevation imagery. It is possible to use agricultural multispectral camera rigs to reconstruct Eucalyptus tree canopy and shrub swamp by combining imagery and selecting appropriate spectral bands for processing.

show abstract

Section: Treesmentioning

confidence: 99%

Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models

Fletcher

Mather

2020

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…( a ) The irradiance restoration based (IRB) method. ( b ) The linear correlation correction (LCC) method [ 16 , 21 ]. ( c ) The light source color rate (LSCR) method [ 33 ].…”

Section: Figurementioning

confidence: 99%

“…Typical IE-based shadow compensation methods include statistical correction (like histogram matching, gamma correction, linear correlation correction (LCC) and gray stretching) [ 13 , 21 , 22 , 23 ], Retinex-based correction [ 24 ], and homomorphic filtering (HF) [ 25 ]. Suzuki et al [ 26 ] presented a dynamic shadow compensation method, which could enhance the visibility of features under shadow regions in urban aerial images.…”

Section: Introductionmentioning

confidence: 99%

“…For testing the shadow compensation performance of our proposed IRB approach, we carried out comparative experiments over test images of WorldView-2 and WorldView-3 acquired at different sites and times. Particularly, we evaluated the shadow compensation performance of the proposed IRB approach both qualitatively and quantitatively against several shadow compensation methods (i.e., LCC [ 16 , 21 ], LSCR [ 33 ], MSR [ 24 , 36 ], HF [ 25 ] and DELM [ 11 , 37 ]) with two WorldView-3 test images of Tripoli, Libya.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images

Han

Huang

et al. 2020

Sensors

View full text Add to dashboard Cite

Numerous applications are hindered by shadows in high resolution satellite remote sensing images, like image classification, target recognition and change detection. In order to improve remote sensing image utilization, significant importance appears for restoring surface feature information under shadow regions. Problems inevitably occur for current shadow compensation methods in processing high resolution multispectral satellite remote sensing images, such as color distortion of compensated shadow and interference of non-shadow. In this study, to further settle these problems, we analyzed the surface irradiance of both shadow and non-shadow areas based on a satellite sensor imaging mechanism and radiative transfer theory, and finally develop an irradiance restoration based (IRB) shadow compensation approach under the assumption that the shadow area owns the same irradiance to the nearby non-shadow area containing the same type features. To validate the performance of the proposed IRB approach for shadow compensation, we tested numerous images of WorldView-2 and WorldView-3 acquired at different sites and times. We particularly evaluated the shadow compensation performance of the proposed IRB approach by qualitative visual sense comparison and quantitative assessment with two WorldView-3 test images of Tripoli, Libya. The resulting images automatically produced by our IRB method deliver a good visual sense and relatively low relative root mean square error (rRMSE) values. Experimental results show that the proposed IRB shadow compensation approach can not only compensate information of surface features in shadow areas both effectively and automatically, but can also well preserve information of objects in non-shadow regions for high resolution multispectral satellite remote sensing images.

show abstract

“…However, often shadows contribute in large parts to the collected data and therefore including them as an additional class seems practical. In the future, it would be useful to test techniques that compensate for shadow areas [56]. Unfortunately, the influence of such techniques on spectral reflectance properties in disease detection and other disciplines is not yet adequately tested.…”

Section: Processing Shadow Areas In Land Cover Classification Problemsmentioning

confidence: 99%

Multispectral, Aerial Disease Detection for Myrtle Rust (Austropuccinia psidii) on a Lemon Myrtle Plantation

Heim

Wright

Scarth

et al. 2019

Drones

View full text Add to dashboard Cite

Disease management in agriculture often assumes that pathogens are spread homogeneously across crops. In practice, pathogens can manifest in patches. Currently, disease detection is predominantly carried out by human assessors, which can be slow and expensive. A remote sensing approach holds promise. Current satellite sensors are not suitable to spatially resolve individual plants or lack temporal resolution to monitor pathogenesis. Here, we used multispectral imaging and unmanned aerial systems (UAS) to explore whether myrtle rust (Austropuccinia psidii) could be detected on a lemon myrtle (Backhousia citriodora) plantation. Multispectral aerial imagery was collected from fungicide treated and untreated tree canopies, the fungicide being used to control myrtle rust. Spectral vegetation indices and single spectral bands were used to train a random forest classifier. Treated and untreated trees could be classified with high accuracy (95%). Important predictors for the classifier were the near-infrared (NIR) and red edge (RE) spectral band. Taking some limitations into account, that are discussedherein, our work suggests potential for mapping myrtle rust-related symptoms from aerial multispectral images. Similar studies could focus on pinpointing disease hotspots to adjust management strategies and to feed epidemiological models.

show abstract

A Review on Various Shadow Detection and Compensation Techniques in Remote Sensing Images

Cited by 51 publications

References 93 publications

Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models

Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models

Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images

Multispectral, Aerial Disease Detection for Myrtle Rust (Austropuccinia psidii) on a Lemon Myrtle Plantation

Contact Info

Product

Resources

About