Improved neighborhood similar pixel interpolator for filling unsacn multi-temporal Landsat ETM+ data without reference

Abstract

Since the scan line corrector (SLC) of the Landsat ETM+ sensor failed permanently in 2003, about 22% of the pixels in an SLC-off image are missed. Traditional gap filling methods always need a SLC-on image for reference, but the most similar sensor (Landsat TM) closed at 2011. And the potential of multi-temporal was also neglected in traditional filling methods. In this paper, a multi-temporal Landsat ETM+ gap filling method is proposed without using SLC-on reference which has ability to increase the utilization efficiency of multi-temporal images. The proposed method is mainly based on neighborhood similar pixel interpolator (NSPI) and the major contribution are find an effective way to select valid temporal and conjunctive use the temporal advantage to calculate of the target pixel value. Similarity both in spatial and temporal can be obtained in our method. Real multi-temporal Landsat data and missing gap location are used to assess the efficacy of the proposed method. Both qualitative and quantitative evaluations results suggest that our proposed method can predict the missing values very accurately and improve the utilization efficiency of multi-temporal.