Abstract
In order to produce better images, darkness identification and detection are essential in remote sensing techniques. Throughout this method, shadow attributes are carefully considered during contrast enhancement, and suspicious darkness is always derived based on the aforementioned image features. Furthermore, a few dark artifacts that could still be misinterpreted as shadows are rejected. The whole feature engineering is completely dependent upon the size of the object as well as their relative positions. The precedent set of the inside and outside highlight profile line (IOHPL) can be used to consider removing reflective surfaces from object categories. IOHPL segmental synchronization results in modules that are relatively homogeneous. Following that, the relatively homogenous sections are used to find the percentage light diagnostic specifications between both the shadow as well as non-shadow regions. This process will result in the effective removal of excess shadows or darkness in satellite-derived aerial urban images.
Similar content being viewed by others
Data availability
These materials created or processed used during proposed investigation are accessible upon mutually agreed from either the principal investigator.
References
Adeline KR, Chen M, Briottet X, Pang SK, Paparoditis N (2013) Shadow detection in very high spatial resolution aerial images: A comparative study. ISPRS J Photogramm Remote Sens 80:21–38
Cai D, Li M, Bao Z, Chen Z, Wei W, Zhang H (2010) Study on shadow detection method on high resolution remote sensing image based on HIS space transformation and NDVI index. In:2010 18th International Conference on Geoinformatics. IEEE, pp 1-4
Chouhan AS, Purohit N, Annaiah H, Saravanan D, Raj EFI, David DS (2021) A real-time gesture based image classification system with FPGA and convolutional neural network. Int J Mod Agric 10(2):2565–2576
Chung KL, Lin YR, Huang YH (2008) Efficient shadow detection of color aerial images based on successive thresholding scheme. IEEE Trans Geosci Remote Sens 47(2):671–682
Dare PM (2005) Shadow analysis in high-resolution satellite imagery of urban areas. Photogramm Eng Remote Sens 71(2):169–177
Deivakani M, Kumar SS, Kumar NU, Raj EFI, Ramakrishna V (2021) VLSI implementation of discrete cosine transform approximation recursive algorithm. In Journal of Physics: Conference Series, vol 1817, no. 1. IOP Publishing, Bristol, p 012017
Farzana FM, Rani E (2019) Technically improved image and video enhancement using adaptive gamma correction with weighing distribution based contrast enhancement techniques. Asian J Appl Sci Technol (AJAST) 3:50–57
Gampala V, Kumar MS, Sushama C, Raj EFI (2020) Deep learning based image processing approaches for image deblurring. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.11.076
Gong J, Sui H, Sun K, Ma G, Liu J (2008)Object-level change detection based on full-scale image segmentation and its application to Wenchuan Earthquake. Sci China Ser E: Technol Sci 51(2):110–122
Guo R, Dai Q, Hoiem D (2011)Single-image shadow detection and removal using paired regions. In CVPR 2011. IEEE, pp 2033-2040
Highnam R, Brady M (1997)Model-based image enhancement of far infrared images. IEEE Trans Pattern Anal Mach Intell 19(4):410–415
Irvin RB, McKeown DM (1989) Methods for exploiting the relationship between buildings and their shadows in aerial imagery. IEEE Trans Syst Man Cybern 19(6):1564–1575
Jain D, Sangale DMD, Raj E (2020) A pilot survey of machine learning techniques in smart grid operations of power systems. Eur J Mol Clin Med 7(7):203–210
Kang X, Huang Y, Li S, Lin H, Benediktsson JA (2017) Extended random walker for shadow detection in very high resolution remote sensing images. IEEE Trans Geosci Remote Sens 56(2):867–876
Li Y, Sasagawa T, Gong P (2004) A system of the shadow detection and shadow removal for high resolution city aerial photo. Proc. ISPRS Congr, Comm, 35, 802-807
Li Y, Gong P, Sasagawa T (2005) Integrated shadow removal based on photogrammetry and image analysis. Int J Remote Sens 26(18):3911–3929
Li H, Zhang L, Shen H (2014) An adaptive nonlocal regularized shadow removal method for aerial remote sensing images. IEEE Trans Geosci Remote Sens 52(1):106–120
Li Z, Shen H, Cheng Q, Liu Y, You S, He Z (2019) Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors. ISPRS J Photogramm Remote Sens 150:197–212
Li X, Li Z, Feng R, Luo S, Zhang C, Jiang M, Shen H (2020) Generating high-quality and high-resolution seamless satellite imagery for large-scale urban regions. Remote Sens 12(1):81
Lorenzi L, Melgani F, Mercier G (2012) A complete processing chain for shadow detection and reconstruction in VHR images. IEEE Trans Geosci Remote Sens 50(9):3440–3452
Luo S, Li H, Shen H (2020) Deeply supervised convolutional neural network for shadow detection based on a novel aerial shadow imagery dataset. ISPRS J Photogramm Remote Sens 167:443–457
Ma H, Qin Q, Shen X (2008) Shadow segmentation and compensation in high resolution satellite images. In: IGARSS 2008-2008 IEEE International Geoscience and Remote Sensing Symposium, vol 2. IEEE, pp II-1036
Makarau A, Richter R, Muller R, Reinartz P (2011) Adaptive shadow detection using a blackbody radiator model. IEEE Trans Geosci Remote Sens 49(6):2049–2059
Mo N, Zhu R, Yan L, Zhao Z (2018) Deshadowing of urban airborne imagery based on object-oriented automatic shadow detection and regional matching compensation. IEEE J Sel Top Appl Earth Obs Remote Sens 11(2):585–605
Priyadarsini K, Raj EFI, Begum AY, Shanmugasundaram V (2020) Comparing DevOps procedures from the context of a systems engineer. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.09.624
Raj EFI, Balaji M (2021) Analysis and classification of faults in switched reluctance motors using deep learning neural networks. Arab J Sci Eng 46(2):1313–1332
Rani E, Grace Priya A, Indiranatchiyar A (2019) Brain tumor detection using ANN classifier. IJETIE 5(9):670–678
Reddy RPK, Nagaraju C (2017) Low Contrast image Shadow removal by using Fuzzy logic technique. Int J Pure Appl Math 114(10):55–63
Shilpa M, Gopalakrishna MT, Naveena C (2020) Approach for shadow detection and removal using machine learning techniques. IET Image Proc 14(13):2998–3005
Shubham K (2021)Covid-19 data analysis for second wave Indian pandemic Seir model by using principal component analysis tool. Turk J Comput Math Educ (TURCOMAT) 12(9):2907–2915
Shun-Ping JI, Yuan XX (2007) A method for shadow detection and change detection of man-made objects. J Remote Sens 11:323–329
Sun C, Chen H, Fan F (2020) Improving accuracy of impervious surface extraction based on a Threshold Hierarchical Method (THM). Appl Sci 10(23):8409
Wang Q, Yan L, Yuan Q, Ma Z (2017) An automatic shadow detection method for VHR remote sensing orthoimagery. Remote Sens 9(5):469
Xu Z, Zhou Y, Wang S, Wang L, Li F, Wang S, Wang Z (2020) A novel intelligent classification method for urban green space based on high-resolution remote sensing images. Remote Sens 12(22):3845
Zhang P, Liu W, Lu H, Shen C (2019) Salient object detection with lossless feature reflection and weighted structural loss. IEEE Trans Image Process 28(6):3048–3060
Zhong Y, Li W, Wang X, Jin S, Zhang L (2020)Satellite-ground integrated destriping network: A new perspective for EO-1 Hyperion and Chinese hyperspectral satellite datasets. Remote Sens Environ 237:111416
Zhou T, Fu H, Sun C, Wang S (2021) Shadow detection and compensation from remote sensing images under complex urban conditions. Remote Sens 13(4):699
Author information
Authors and Affiliations
Contributions
Mrs. E. Francy Irudaya Rani- Writing - Original draft, Software and Validation.
Dr. T. Lurthu Pushparaj - Methodology, and Conceptualization.
Mr. E. Fantin Irudaya Raj - Review & Editing, Investigation and Supervision.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest on this paper.
Consent to participation
Not applicable.
Consent to publish
Not applicable.
Additional information
Communicated by: H. Babaie.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Rani, E.F.I., Pushparaj, T.L. & Raj, E.F.I. Escalating the resolution of an urban aerial image via novel shadow amputation algorithm. Earth Sci Inform 15, 905–913 (2022). https://doi.org/10.1007/s12145-022-00772-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12145-022-00772-0