NDLI: Recovering defective Landsat 7 Enhanced Thematic Mapper Plus images via multiple linear regression model

Content Provider	IET Digital Library
Author	Sadiq, Asmaa Sulong, Ghazali Edwar, Loay
Abstract	Since 2003, the scan line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor has failed permanently, inhibiting the retrieval or scanning of 22% of the pixels in each Landsat 7 SLC-off image. This utter failure has seriously limited the scientific applications and usability of ETM+ data. Precise and complete recovery of the missing pixels for the Landsat 7 SLC-off images is a challenging issue and developing an efficient gap-fill algorithm with improved ETM+ data usability has been ever-demanding. In this study, a new gap filling method has been introduced to reconstruct the SLC-off images via multi-temporal SLC-off auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two auxiliary fill images in parallel using the multiple linear regressions model. Both simulated and actual defective Landsat 7 images were tested to assess the performance of the proposed model by comparing with two multi-temporal data based methods, the local linear histogram matching method and Neighbourhood Similar Pixel Interpolator method. The quantitative evaluations indicate that the proposed method makes an accurate estimate of the missing values even for more temporally distant fill images.
Starting Page	788
Ending Page	797
Page Count	10
ISSN	17519632
Volume Number	10
e-ISSN	17519640
Issue Number	Issue 8, Dec (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/10/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0009
Journal	IET Computer Vision
Publisher Date	2016-05-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Artificial Satellites Computer Vision And Image Processing Technique Data And Information; Acquisition, Processing, Storage And Dissemination in Geophysics Defective Landsat 7 Enhanced Thematic Mapper Plus Image Recovery ETM+ Data Usability Gap Filling Method Geography And Cartography Computing Geophysical Image Processing Geophysical Technique And Equipment Image Enhancement Image Reconstruction Image Resolution Image Sonsor Infrared Imaging Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Landsat 7 Enhanced Thematic Mapper Plus Sensor Landsat 7 SLC-off Image Missing Value Estimation Multiple Linear Regression Model Optical, Image And Video Signal Processing Probability Theory Regression Analysis Remote Sensing Scan Line Corrector Statistics Stochastic Linearised SCUC
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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Spatial resolution to landsat-7 enhanced thematic mapper plus (2000).

Geometric Calibration Updates to Landsat 7 ETM+ Instrument for Landsat Collection 2 Products

Radiometric Characteristics of the Landsat Collection 1 Dataset

Enhanced thematic mapper plus (etm+) contain important.

Radiometric Cross Calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization

Landsat tm and etm+ thermal band calibration.

Landsat sensor cross-calibration using nearly-coincident matching scenes.

Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches

Recovering defective Landsat 7 Enhanced Thematic Mapper Plus images via multiple linear regression model

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