Gap-Filling Restoration Methods for ETM+ Sensor Images

Abstract

Enhanced Thematic Mapper Plus (ETM+) onboard the Landsat-7 remotely sensor satellite was launched on 15 April 1999. On May 31, 2003, image acquisition via the ETM+ was greatly impacted by the failure of the system’s Scan Line Corrector (SLC). Consequently, the ETM+ has lost approximately 22% of the data due to the increased scan gap. In this work, several gap-filling methods will be proposed to restore the ETM+ image malfunctions. Some of the proposed methods will be carried by estimating the missed pixel’s values from the same image pixel’s neighborhood, while others will utilize the pixel values extracted from different temporal scene acquired in different time. Mean average filter, median filter, midpoint filter, and several interpolations (e.g. 1D-nearest neighbor, 1D-linear, and 1D-cubic-spline interpolations) techniques will be utilized to estimate the missed pixel’s values from the same malfunction scene and from different temporally radiance corrected scene. Additionally, the Linear Local Histogram Matching (LLHM) technique will be implemented to fill the gaps by gain-bias method and by gray-level normalization methods, using the whole image values first, and a window’s values second.