Evaluation of Shadow Reconstruction Algorithm for Very High Resolution Satellite Imagery

Panchal Anjali Jayant, Rizvi Imdad A., Kadam M.M., (doi: 10.23953/cloud.ijarsg.38)


The Very High Resolution images have opened a new era for remote sensing applications such as object detection, classification, object mapping and change detection. However, the effects of shadow in these images are remarkable. The objective of this paper is to propose algorithm for shadow reconstruction. The primer stage, shadow detection and classification are carried out which separates shadow from rest of environment. For doing reconstruction the preprocessing is done by morphological operations which extract image components such as region and shape. It is followed by border creation and finally the reconstructed of an original image is accomplished border interpolation. The reconstruction accuracy is calculated by using Kappa Coefficient. Here Experimental results are obtained on three VHR images representing different shadow conditions. The performance analysis is carried out which shows better sensitivity and specificity.


Cast Shadow; Self-Shadow; Shadow Detection; Sensitivity; Specificity; VHR Satellite Images

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*2016 Journal Impact Factor was established by dividing the number of articles published in 2014 and 2015 with the number of times they are cited in 2016 based on Google Scholar, Google Search and the Microsoft Academic Search. If ‘A’ is the total number of articles published in 2014 and 2015, and ‘B’ is the number of times these articles were cited in indexed publications during 2016 then, journal impact factor = A/B. To know More: (http://en.wikipedia.org/wiki/Impact_factor)