Reconstruction the Missing Pixels for Landsat ETM+SLC-off Images Using Multiple Linear Regression Model

On 31 May 2003, the scan line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor which compensates for the forward motion of the satellite in the imagery acquired  failed permanently, resulting in loss of the ability to scan about 20% of the pixels in each Landsat 7 SLC-off image. This permanent failure has seriously hampered the scientific applications of ETM+ images. In this study, an innovative gap filling approach has been introduced to recover the missing pixels in the SLC-off images using multi-temporal ETM+ SLC-off auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two fill images in parallel using the multiple linear regressions (MLR) model. Simulated and actual SLC-off ETM+ images were used to assess the performance of the proposed method by comparing with multi-temporal data based methods, the LLHM method which is based on simple linear regression (SLR) model. The qualitative and quantitative evaluations indicate that the proposed method can recover the value of un-scanned pixels accurately, especially in heterogeneous landscape and even with more temporally distant fill images.

[1]  Yi Jiang,et al.  A Comparison Study of Missing Value Processing Methods in Time Series Data Mining , 2009, 2009 International Conference on Computational Intelligence and Software Engineering.

[2]  Wei Hu,et al.  A new method of restoring ETM+ SLC-off images based on multi-temporal images , 2011, 2011 19th International Conference on Geoinformatics.

[3]  Martin Kappas,et al.  Multi-source image reconstruction: exploitation of EO-1/ALI in Landsat-7/ETM+ SLC-off gap filling , 2008, Electronic Imaging.

[4]  Feng Chen,et al.  Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches , 2012 .

[5]  Feng Chen,et al.  Exploitation of CBERS-02B as auxiliary data in recovering the Landsat7 ETM+ SLC-off image , 2010, 2010 18th International Conference on Geoinformatics.

[6]  J. Storey,et al.  LANDSAT 7 SCAN LINE CORRECTOR-OFF GAP-FILLED PRODUCT DEVELOPMENT , 2005 .

[7]  Chao Zeng,et al.  Recovering missing pixels for Landsat ETM + SLC-off imagery using multi-temporal regression analysis and a regularization method , 2013 .

[8]  David W. S. Wong,et al.  An adaptive inverse-distance weighting spatial interpolation technique , 2008, Comput. Geosci..

[9]  Mobasheri Mohammad Reza,et al.  Using IRS Products to Recover 7ETM+ Defective Images , 2008 .

[10]  Valeria Rulloni,et al.  Large gap imputation in remote sensed imagery of the environment , 2010, Comput. Stat. Data Anal..

[11]  Darrel L. Williams,et al.  Landsat sensor performance: history and current status , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Ghazali Sulong,et al.  Survey on gap filling algorithms in Landsat 7 ETM+ images , 2014 .

[13]  D. Roy,et al.  Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data , 2008 .

[14]  S. Maxwell,et al.  Photogrammetric Engineering & Remote Sensing Filling Landsat Etm+ Slc-off Gaps Using a Segmentation Model Approach Case Study , 2022 .

[15]  Sathit Prasomphan Imputing Landsat7 ETM+ with SLC-off image using the similarity measurement between two clusters , 2012, The First International Conference on Future Generation Communication Technologies.

[16]  Lina Tang,et al.  Recovering of the thermal band of Landsat 7 SLC-off ETM+ image using CBERS as auxiliary data , 2011 .

[17]  Wei Shao,et al.  Parallel maximum likelihood estimator for multiple linear regression models , 2015, J. Comput. Appl. Math..

[18]  Michael Schmidt,et al.  Geostatistical interpolation of SLC-off Landsat ETM+ images , 2009 .

[19]  Xiaolin Zhu,et al.  MAP-MRF Approach to Landsat ETM+ SLC-Off Image Classification , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Bandu N. Pamadi Cramer's Rule , 2004 .

[21]  supM.A.K. Sadiq,et al.  Single and Multi-source Methods for Reconstruction the Gaps in Landsat 7 ETM+ SLC-off Images , 2015 .

[22]  Gang Yang,et al.  Missing Information Reconstruction of Remote Sensing Data: A Technical Review , 2015, IEEE Geoscience and Remote Sensing Magazine.

[23]  Hamid Reza Pourghasemi,et al.  Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province, Iran , 2014, Arabian Journal of Geosciences.

[24]  Jin Chen,et al.  A new geostatistical approach for filling gaps in Landsat ETM+ SLC-off images , 2012 .

[25]  Feng Gao,et al.  A simple and effective method for filling gaps in Landsat ETM+ SLC-off images , 2011 .

[26]  Mazlan Hashim,et al.  Assessment of Landsat 7 Scan Line Corrector-off data gap-filling methods for seagrass distribution mapping , 2015 .

[27]  Weidong Li,et al.  Gaps‐fill of SLC‐off Landsat ETM+ satellite image using a geostatistical approach , 2007 .

[28]  G. L. Schmidt,et al.  A multi‐scale segmentation approach to filling gaps in Landsat ETM+ SLC‐off images , 2007 .

[29]  Martin Kappas,et al.  Multi-Source Remotely Sensed Data Combination: Projection Transformation Gap-Fill Procedure , 2008, Sensors.

[30]  Joanne C. White,et al.  Evaluation of Landsat-7 SLC-off image products for forest change detection , 2008 .

[31]  Amit Ganatra,et al.  Survey on Gap Filling in Satellite Images and Inpainting Algorithm , 2012 .

[32]  Xue Wang,et al.  Research on Algorithms for Recovering Landsat - 7 Gap Data , 2011, 2011 International Conference on Control, Automation and Systems Engineering (CASE).