Fusion of landsat and worldview images

Pansharpened Landsat images have 15 m spatial resolution with 16-day revisit periods. On the other hand, Worldview images have 0.5 m resolution after pansharpening but the revisit times are uncertain. We present some preliminary results for a challenging image fusion problem that fuses Landsat and Worldview (WV) images to yield a high temporal resolution image sequence at the same spatial resolution of WV images. Since the spatial resolution between Landsat and Worldview is 30 to 1, our preliminary results are mixed in that the objective performance metrics such as peak signal-to-noise ratio (PSNR), correlation coefficient (CC), etc. sometimes showed good fusion performance, but at other times showed poor results. This indicates that more fusion research is still needed in this niche application.

[1]  Chiman Kwan,et al.  Mars Surface Mineral Abundance Estimation Using THEMIS and TES Images , 2018, 2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

[2]  Mathew R. Schwaller,et al.  On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Jocelyn Chanussot,et al.  A Critical Comparison Among Pansharpening Algorithms , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Chiman Kwan,et al.  Enhancing Mastcam Images for Mars Rover Mission , 2017, ISNN.

[5]  Chiman Kwan,et al.  Remote Sensing Performance Enhancement in Hyperspectral Images , 2018, Sensors.

[6]  Feng Gao,et al.  A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction , 2018, Remote. Sens..

[7]  Hairong Qi,et al.  Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[8]  Chiman Kwan,et al.  Mastcam image enhancement using estimated point spread functions , 2017, 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON).

[9]  Chiman Kwan,et al.  Blind Quality Assessment of Fused WorldView-3 Images by Using the Combinations of Pansharpening and Hypersharpening Paradigms , 2017, IEEE Geoscience and Remote Sensing Letters.

[10]  Naoto Yokoya,et al.  Hyperspectral Pansharpening: A Review , 2015, IEEE Geoscience and Remote Sensing Magazine.

[11]  Chiman Kwan.  Image Resolution Enhancement for Remote Sensing Applications , 2018, ICVISP.

[12]  Chiman Kwan,et al.  A Super-Resolution and Fusion Approach to Enhancing Hyperspectral Images , 2018, Remote. Sens..

[13]  Michael A. Lefsky,et al.  A flexible spatiotemporal method for fusing satellite images with different resolutions , 2016 .

[14]  Yuzhong Shen,et al.  Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images , 2018, Sensors.

[15]  Yuzhong Shen,et al.  Simple and effective cloud- and shadow-detection algorithms for Landsat and Worldview images , 2020, Signal Image Video Process..

[16]  Chiman Kwan,et al.  Resolution enhancement for hyperspectral images: A super-resolution and fusion approach , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[17]  Chiman Kwan,et al.  On the generation of high-spatial and high-spectral resolution images using THEMIS and TES for Mars exploration , 2018, Defense + Security.

[18]  Chiman Kwan,et al.  Fusion of themis and TES for accurate Mars surface characterization , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[19]  Chiman Kwan,et al.  Hyperspectral image super-resolution: a hybrid color mapping approach , 2016 .

[20]  Chiman Kwan,et al.  Pansharpening of Mastcam images , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).