Cloud Detection and Cloud Removal of Satellite Image—A Case Study

The book contributes to the subject area of remote sensing and Geographic Information System. It is focused on the study and analysis of automated cloud detection and removal of satellite imagery using the selection of thresholds value for various spectral tests in the perspective of RSGIS (Ramya, KarthiPrem, Nithyasri in IJIACS 3(2), [1], Rafael, Richard in Digital image processing. Prentice Hall, [2]). A significant obstacle of extracting information using satellite imagery is the presence of clouds. Removing these portions of image and then filling in the missing data is an important image-editing task. Traditionally, the objective is to cut the cloudy portions out from the frame and fill in the gaps with clear patches from similar images taken at different time. Remote sensing is providing opportunities in various branches of environmental research. The fields of application for multi-spectral remote sensing instruments in earth observation are monitoring the forests, oceans or urban areas over agricultural applications to the extent of natural resources. A significant prerequisite for analysis of earth observation data is the information that is free from external influences and disturbances. One possible cause of data loss is cloud cover of satellite imagery. Cloud cover is recognized as a significant loss of data and information quality by many scientific studies. The existence of cloud cover is the loss of meaningful data and information because they are a considerable source of uncertainty with regard to the application of any algorithm aiming for the retrieval of land surface (Zakaria, Ibrahim, Suandi in A review: image compensation techniques. pp. 404–408, [3], Sengee, Sengee, Choi in IEEE Trans Consum Electron 56(4):2727–2734, [4], Hardin, Jensen, Long, Remund in Testing two cloud removal algorithms for SSM/I [5]).