What is it about?
The paper presents a new multi-temporal recovering approach for estimating the missing values in ETM+ SLC-off images based on Multiple Linear Regression (MLR) model by exploiting information fro two SLC-off images in parallel.
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Why is it important?
The paper perform multi-temporal reconstruction method that is based on (MLR) models to precisely recover the mostly degraded pixels by exploiting information derived from two multi-temporal SLC-off fill images simultaneously; by building a linear regression between the target missing pixels in target image and the corresponding pixels in both two auxiliary fill images in parallel rather than using the fill images in progressive as in most multi-temporal approaches.
Perspectives
It is important to mention that in this paper the proposed method that based on using two fill images simultaneously by utilizing MLR model was tested and evaluated on gap locations with (6-8) pixels and the results demonstrate good performance, also I want to clarify that further experiments are still ongoing to employed this proposed model to fill in the large gap with (12-13) pixels width.
Asmaa Abdul Jabar
higher education
Read the Original
This page is a summary of: Recovering defective Landsat 7 Enhanced Thematic Mapper Plus images via multiple linear regression model, IET Computer Vision, December 2016, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-cvi.2016.0009.
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