Cloud cover automatic detection assessment for THAICHOTE satellite images

The Earth observation optical image is considered as the excellent applicant to extract the Earth's surface information. Cloud cover is a spectacular problem for land surface analysis. False detection and analysis typically results from even small percentages of cloud cover. Therefore knowing the percentage of cloud in the image is constructive for the user to allow for selection of those images that contain an acceptable amount of cloud cover (and therefore error) for their application. This paper presents the algorithm for cloud cover assessment using ROI (region of interest) image classification based on histogram segmentation for THAICHOTE satellite images. The objective is to accurately determine the percentage of cloud cover in the optical satellite image, which is improved from the existing algorithm developed. In addition the morphology structure element is used in the algorithm. A study on the appropriate shape and size of structure element is required and has been discussed in this paper.