Adjacency effect correction of optical satellite image with sub-meter spatial resolution Article Swipe
Tao Wang
,
Nan Zhou
,
Weining Yi
,
Jin Hong
,
Xiao Liu
,
Xin Li
,
Quan Zhang
,
Shiyu Liu
,
Zhaozhou Li
,
Kaitao Li
,
Wenyu Cui
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7498/aps.70.20202187
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7498/aps.70.20202187
The adjacency effect, the contribution of the neighboring pixels to the radiance of the line of sight pixel, is caused by the Rayleigh scattering of atmospheric molecules and Mie scattering of aerosol particles. The adjacency effect will cause the reflectance of each pixel in the apparent reflectance satellite image to be between the real reflectance and the average background reflectance, reducing the accuracy of the surface reflectance inversion. Therefore, it is very important to remove the adjacency effect to improve the accuracy of retrieving the surface reflectance from satellite images. The most critical issue of the adjacency effect is to accurately calculate the weight of the contribution of each background pixel to the adjacency effect. The weight value of the contribution of each background pixel to the adjacency effect mainly depends on the spatial distance between the target pixel and the background pixel, the difference in reflectance between the target pixel and the background pixel, and the optical thickness of atmospheric molecules and the optical thickness of aerosol. At present, the commonly used weight function for calculating the weight value considers only the influence of optical thickness and spatial distance on the weight value. These weight functions are applied to a relatively uniform surface. However, when these weight functions are applied to an inhomogeneous surface, they will greatly reduce the accuracy of the adjacency effect correction. The combination of ground features in satellite images with the sub-meter spatial resolution is complex, so the influence of the difference in reflectance between the target pixel and the background pixel on the adjacency effect must be considered. The adaptive atmospheric correction algorithm proposed in this paper can adjust the weight value of the contribution of background pixels to the adjacency effect according to the spatial distance between the target pixel and the background pixel, the difference in reflectance between the target pixel and the background pixel, and the difference between the atmospheric molecules’ optical thickness and aerosol optical thickness. The adaptive atmospheric correction algorithm is used to correct the adjacency effect on GF-2 panchromatic satellite images. The results show that the adaptive atmospheric correction algorithm can effectively remove the adjacency effect in sub-meter spatial resolution optical satellite images, improve both the accuracy of quantitative study and the satellite image quality.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7498/aps.70.20202187
- https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.70.20202187.pdf
- OA Status
- diamond
- Cited By
- 4
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3174141080
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- OpenAlex ID
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https://openalex.org/W3174141080Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.7498/aps.70.20202187Digital Object Identifier
- Title
-
Adjacency effect correction of optical satellite image with sub-meter spatial resolutionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
-
Tao Wang, Nan Zhou, Weining Yi, Jin Hong, Xiao Liu, Xin Li, Quan Zhang, Shiyu Liu, Zhaozhou Li, Kaitao Li, Wenyu CuiList of authors in order
- Landing page
-
https://doi.org/10.7498/aps.70.20202187Publisher landing page
- PDF URL
-
https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.70.20202187.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
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-
diamondOpen access status per OpenAlex
- OA URL
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https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.70.20202187.pdfDirect OA link when available
- Concepts
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Metre, Satellite, Remote sensing, Image resolution, Adjacency list, Optics, Satellite image, Resolution (logic), Computer science, Image (mathematics), Physics, Computer vision, Artificial intelligence, Astronomy, Geology, AlgorithmTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
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2024: 3, 2023: 1Per-year citation counts (last 5 years)
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18Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.it | 69 |
| abstract_inverted_index.of | 5, 12, 15, 24, 30, 40, 63, 82, 94, 104, 107, 118, 121, 159, 166, 184, 221, 228, 244, 278, 281, 369 |
| abstract_inverted_index.on | 131, 190, 257, 338 |
| abstract_inverted_index.so | 241 |
| abstract_inverted_index.to | 9, 49, 73, 78, 99, 111, 125, 199, 211, 284, 289, 333 |
| abstract_inverted_index.Mie | 28 |
| abstract_inverted_index.The | 0, 33, 90, 115, 226, 264, 326, 343 |
| abstract_inverted_index.and | 27, 55, 139, 151, 155, 162, 187, 253, 297, 309, 313, 322, 372 |
| abstract_inverted_index.are | 197, 209 |
| abstract_inverted_index.can | 273, 352 |
| abstract_inverted_index.for | 175 |
| abstract_inverted_index.the | 3, 6, 10, 13, 21, 38, 44, 52, 56, 61, 64, 75, 80, 84, 95, 102, 105, 112, 119, 126, 132, 136, 140, 143, 148, 152, 156, 163, 170, 177, 182, 191, 219, 222, 235, 242, 245, 250, 254, 258, 275, 279, 285, 290, 294, 298, 301, 306, 310, 314, 317, 335, 347, 355, 367, 373 |
| abstract_inverted_index.GF-2 | 339 |
| abstract_inverted_index.both | 366 |
| abstract_inverted_index.each | 41, 108, 122 |
| abstract_inverted_index.from | 87 |
| abstract_inverted_index.line | 14 |
| abstract_inverted_index.most | 91 |
| abstract_inverted_index.must | 261 |
| abstract_inverted_index.only | 181 |
| abstract_inverted_index.real | 53 |
| abstract_inverted_index.show | 345 |
| abstract_inverted_index.that | 346 |
| abstract_inverted_index.they | 215 |
| abstract_inverted_index.this | 271 |
| abstract_inverted_index.used | 172, 332 |
| abstract_inverted_index.very | 71 |
| abstract_inverted_index.when | 205 |
| abstract_inverted_index.will | 36, 216 |
| abstract_inverted_index.with | 234 |
| abstract_inverted_index.These | 194 |
| abstract_inverted_index.cause | 37 |
| abstract_inverted_index.image | 48, 375 |
| abstract_inverted_index.issue | 93 |
| abstract_inverted_index.paper | 272 |
| abstract_inverted_index.pixel | 42, 110, 124, 138, 150, 252, 256, 296, 308 |
| abstract_inverted_index.sight | 16 |
| abstract_inverted_index.study | 371 |
| abstract_inverted_index.these | 206 |
| abstract_inverted_index.value | 117, 179, 277 |
| abstract_inverted_index.adjust | 274 |
| abstract_inverted_index.caused | 19 |
| abstract_inverted_index.effect | 35, 77, 97, 128, 224, 260, 287, 337, 357 |
| abstract_inverted_index.ground | 229 |
| abstract_inverted_index.images | 233 |
| abstract_inverted_index.mainly | 129 |
| abstract_inverted_index.pixel, | 17, 142, 154, 300, 312 |
| abstract_inverted_index.pixels | 8, 283 |
| abstract_inverted_index.reduce | 218 |
| abstract_inverted_index.remove | 74, 354 |
| abstract_inverted_index.target | 137, 149, 251, 295, 307 |
| abstract_inverted_index.value. | 193 |
| abstract_inverted_index.weight | 103, 116, 173, 178, 192, 195, 207, 276 |
| abstract_inverted_index.aerosol | 31, 323 |
| abstract_inverted_index.applied | 198, 210 |
| abstract_inverted_index.average | 57 |
| abstract_inverted_index.between | 51, 135, 147, 249, 293, 305, 316 |
| abstract_inverted_index.correct | 334 |
| abstract_inverted_index.depends | 130 |
| abstract_inverted_index.effect, | 2 |
| abstract_inverted_index.effect. | 114 |
| abstract_inverted_index.greatly | 217 |
| abstract_inverted_index.images, | 364 |
| abstract_inverted_index.images. | 89, 342 |
| abstract_inverted_index.improve | 79, 365 |
| abstract_inverted_index.optical | 157, 164, 185, 320, 324, 362 |
| abstract_inverted_index.results | 344 |
| abstract_inverted_index.spatial | 133, 188, 237, 291, 360 |
| abstract_inverted_index.surface | 65, 85 |
| abstract_inverted_index.uniform | 202 |
| abstract_inverted_index.However, | 204 |
| abstract_inverted_index.Rayleigh | 22 |
| abstract_inverted_index.accuracy | 62, 81, 220, 368 |
| abstract_inverted_index.adaptive | 265, 327, 348 |
| abstract_inverted_index.aerosol. | 167 |
| abstract_inverted_index.apparent | 45 |
| abstract_inverted_index.commonly | 171 |
| abstract_inverted_index.complex, | 240 |
| abstract_inverted_index.critical | 92 |
| abstract_inverted_index.distance | 134, 189, 292 |
| abstract_inverted_index.features | 230 |
| abstract_inverted_index.function | 174 |
| abstract_inverted_index.present, | 169 |
| abstract_inverted_index.proposed | 269 |
| abstract_inverted_index.quality. | 376 |
| abstract_inverted_index.radiance | 11 |
| abstract_inverted_index.reducing | 60 |
| abstract_inverted_index.surface, | 214 |
| abstract_inverted_index.surface. | 203 |
| abstract_inverted_index.according | 288 |
| abstract_inverted_index.adjacency | 1, 34, 76, 96, 113, 127, 223, 259, 286, 336, 356 |
| abstract_inverted_index.algorithm | 268, 330, 351 |
| abstract_inverted_index.calculate | 101 |
| abstract_inverted_index.considers | 180 |
| abstract_inverted_index.functions | 196, 208 |
| abstract_inverted_index.important | 72 |
| abstract_inverted_index.influence | 183, 243 |
| abstract_inverted_index.molecules | 26, 161 |
| abstract_inverted_index.satellite | 47, 88, 232, 341, 363, 374 |
| abstract_inverted_index.sub-meter | 236, 359 |
| abstract_inverted_index.thickness | 158, 165, 186, 321 |
| abstract_inverted_index.Therefore, | 68 |
| abstract_inverted_index.accurately | 100 |
| abstract_inverted_index.background | 58, 109, 123, 141, 153, 255, 282, 299, 311 |
| abstract_inverted_index.correction | 267, 329, 350 |
| abstract_inverted_index.difference | 144, 246, 302, 315 |
| abstract_inverted_index.inversion. | 67 |
| abstract_inverted_index.particles. | 32 |
| abstract_inverted_index.relatively | 201 |
| abstract_inverted_index.resolution | 238, 361 |
| abstract_inverted_index.retrieving | 83 |
| abstract_inverted_index.scattering | 23, 29 |
| abstract_inverted_index.thickness. | 325 |
| abstract_inverted_index.atmospheric | 25, 160, 266, 318, 328, 349 |
| abstract_inverted_index.calculating | 176 |
| abstract_inverted_index.combination | 227 |
| abstract_inverted_index.considered. | 263 |
| abstract_inverted_index.correction. | 225 |
| abstract_inverted_index.effectively | 353 |
| abstract_inverted_index.neighboring | 7 |
| abstract_inverted_index.reflectance | 39, 46, 54, 66, 86, 146, 248, 304 |
| abstract_inverted_index.contribution | 4, 106, 120, 280 |
| abstract_inverted_index.molecules’ | 319 |
| abstract_inverted_index.panchromatic | 340 |
| abstract_inverted_index.quantitative | 370 |
| abstract_inverted_index.reflectance, | 59 |
| abstract_inverted_index.inhomogeneous | 213 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 11 |
| citation_normalized_percentile.value | 0.68914494 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |