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license: unknown |
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# Description |
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ICVL is a hyperspectral image dataset, collected by "[Sparse Recovery of Hyperspectral Signal from Natural RGB Images](http://link.springer.com/chapter/10.1007/978-3-319-46478-7_2)" |
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The database images were acquired using a Specim PS Kappa DX4 hyperspectral camera and a rotary stage for spatial scanning. At this time it contains 200 images and will continue to grow progressively. |
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Images were collected at 1392 $\times$ 1300 spatial resolution over 519 spectral bands (400-1,000nm at roughly 1.25nm increments). The .raw files contain raw out-of-camera data in ENVI format and .hdr files contain the headers required to decode them. For your convenience, .mat files are provided, downsampled to 31 spectral channels from 400nm to 700nm at 10nm increments. |
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The original dataset only contains clean images. For hyperspectral image denoising benchmarks, the testing datasets come from "3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising". |
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# Quick look |
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|---|---------|-----------|-------------| |
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| 4cam_0411-1640-1 |4cam_0411-1648 |bguCAMP_0514-1659 |bguCAMP_0514-1711 | |
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| bguCAMP_0514-1712 |bguCAMP_0514-1718 |bguCAMP_0514-1723 |bguCAMP_0514-1724 | |
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| BGU_0403-1419-1 |bgu_0403-1439 |bgu_0403-1444 |bgu_0403-1459 | |
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| bgu_0403-1511 |bgu_0403-1523 |bgu_0403-1525 |BGU_0522-1113-1 | |
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| BGU_0522-1127 |BGU_0522-1136 |BGU_0522-1201 |BGU_0522-1203 | |
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| BGU_0522-1211 |BGU_0522-1216 |BGU_0522-1217 |bulb_0822-0903 | |
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| bulb_0822-0909 |CC_40D_2_1103-0917 |eve_0331-1549 |eve_0331-1551 | |
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| eve_0331-1601 |eve_0331-1602 |eve_0331-1606 |eve_0331-1618 | |
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| eve_0331-1632 |eve_0331-1633 |eve_0331-1646 |eve_0331-1647 | |
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| eve_0331-1656 |eve_0331-1657 |eve_0331-1702 |eve_0331-1705 | |
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| Flower_0325-1336 |gavyam_0823-0930 |gavyam_0823-0933 |gavyam_0823-0944 | |
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| gavyam_0823-0945 |gavyam_0823-0950-1 |grf_0328-0949 |hill_0325-1219 | |
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| hill_0325-1228 |hill_0325-1235 |hill_0325-1242 |IDS_COLORCHECK_1020-1215-1 | |
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| IDS_COLORCHECK_1020-1223 |Labtest_0910-1502 |Labtest_0910-1504 |Labtest_0910-1506 | |
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| Labtest_0910-1509 |Labtest_0910-1510 |Labtest_0910-1511 |Labtest_0910-1513 | |
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| lehavim_0910-1600 |lehavim_0910-1602 |lehavim_0910-1605 |lehavim_0910-1607 | |
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| lehavim_0910-1610 |Lehavim_0910-1622 |Lehavim_0910-1626 |Lehavim_0910-1627 | |
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| Lehavim_0910-1629 |Lehavim_0910-1630 |Lehavim_0910-1633 |Lehavim_0910-1635 | |
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| Lehavim_0910-1636 |Lehavim_0910-1640 |Lehavim_0910-1708 |Lehavim_0910-1716 | |
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| Lehavim_0910-1717 |Lehavim_0910-1718 |Lehavim_0910-1725 |lst_0408-0950 | |
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| lst_0408-1004 |lst_0408-1012 |Master20150112_f2_colorchecker |Master2900k | |
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| Master5000K |Master5000K_2900K |Maz0326-1038 |maz_0326-1048 | |
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| mor_0328-1209-2 |nachal_0823-1038 |nachal_0823-1040 |nachal_0823-1047 | |
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| nachal_0823-1110 |nachal_0823-1117 |nachal_0823-1118 |nachal_0823-1121 | |
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| nachal_0823-1127 |nachal_0823-1132 |nachal_0823-1144 |nachal_0823-1145 | |
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| nachal_0823-1147 |nachal_0823-1149 |nachal_0823-1152 |nachal_0823-1210-4 | |
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| nachal_0823-1213 |nachal_0823-1214 |nachal_0823-1217 |nachal_0823-1220 | |
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| nachal_0823-1222 |nachal_0823-1223 |negev_0823-1003 |negev_0823-1005 | |
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| objects_0924-1550 |objects_0924-1556 |objects_0924-1557 |objects_0924-1558 | |
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| objects_0924-1600 |objects_0924-1601 |objects_0924-1602 |objects_0924-1605 | |
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| objects_0924-1607 |objects_0924-1610 |objects_0924-1611 |objects_0924-1612 | |
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| objects_0924-1614 |objects_0924-1617 |objects_0924-1619 |objects_0924-1620 | |
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| objects_0924-1622 |objects_0924-1628 |objects_0924-1629 |objects_0924-1631 | |
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| objects_0924-1632 |objects_0924-1633 |objects_0924-1634 |objects_0924-1636 | |
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| objects_0924-1637 |objects_0924-1638 |objects_0924-1639 |objects_0924-1641 | |
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| objects_0924-1645 |objects_0924-1648 |objects_0924-1650 |objects_0924-1652 | |
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| omer_0331-1055 |omer_0331-1102 |omer_0331-1104 |omer_0331-1118 | |
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| omer_0331-1119 |omer_0331-1130 |omer_0331-1131 |omer_0331-1135 | |
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| omer_0331-1150 |omer_0331-1159 |peppers_0503-1308 |peppers_0503-1311 | |
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| peppers_0503-1315 |peppers_0503-1330 |peppers_0503-1332 |pepper_0503-1228 | |
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| pepper_0503-1229 |pepper_0503-1236 |plt_0411-1037 |plt_0411-1046 | |
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| plt_0411-1116 |plt_0411-1155 |plt_0411-1200-1 |plt_0411-1207 | |
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| plt_0411-1210 |plt_0411-1211 |plt_0411-1232-1 |prk_0328-0945 | |
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| prk_0328-1025 |prk_0328-1031 |prk_0328-1034 |prk_0328-1037 | |
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| prk_0328-1045 |rsh2_0406-1505 |rsh_0406-1343 |rsh_0406-1356 | |
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| rsh_0406-1413 |rsh_0406-1427 |rsh_0406-1441-1 |rsh_0406-1443 | |
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| sami_0331-1019 |sat_0406-1107 |sat_0406-1129 |sat_0406-1130 | |
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| sat_0406-1157-1 |selfie_0822-0906 |strt_0331-1027 |tree_0822-0853 | |
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| ulm_0328-1118 | | | | |
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# Credits |
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Dataset originally collected by ICVL from the webpage: |
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https://icvl.cs.bgu.ac.il/pages/researches/hyperspectral-imaging.html |
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For questions, comments and technical assistance, please contact [[email protected]](mailto:[email protected]) |
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When used, fully or partially, please cite: |
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``` |
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Arad and Ben-Shahar, Sparse Recovery of Hyperspectral Signal from Natural RGB Images, in the European Conference on Computer Vision, Amsterdam, The Netherlands, October 11–14, 2016 |
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``` |
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Bibtex: |
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``` |
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@inproceedings{arad_and_ben_shahar_2016_ECCV, |
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title={Sparse Recovery of Hyperspectral Signal from Natural RGB Images}, |
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author={Arad, Boaz and Ben-Shahar, Ohad}, |
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booktitle={European Conference on Computer Vision}, |
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pages={19--34}, |
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year={2016}, |
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organization={Springer} |
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} |
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``` |
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