IEEE Geoscience and Remote Sensing Magazine - December 2021 - 31

Pattern Recognit. (CVPR), 2018, pp. 6154-6162. doi: 10.1109/
CVPR.2018.00644.
[91] K. Chen et al., " Hybrid task cascade for instance segmentation, "
in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR),
2019, pp. 4974-4983. doi: 10.1109/CVPR.2019.00511.
[92] J. Redmon and A. Farhadi, " YOLO9000: Better, faster, stronger, "
in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR),
2017, pp. 6517-6525. doi: 10.1109/CVPR.2017.690.
[93] J. Redmon and A. Farhadi, " YOLOv3: An incremental improvement, "
2018. [Online]. Available: http://arxiv.org/abs/1804.02767
[94] H. Law and J. Deng, " CornerNet: Detecting objects as paired
keypoints, " in Proc. 15th Euro. Conf. Comput. Vis., 2018, pp.
765-781.
[95] A. Newell, K. Yang, and J. Deng, " Stacked hourglass networks
for human pose estimation, " in Proc. 14th Euro. Conf. Comput.
Vis., Amsterdam, The Netherlands, 2016, pp. 483-499.
[96] K. Duan, S. Bai, L. Xie, H. Qi, Q. Huang, and Q. Tian, " Centernet:
Keypoint triplets for object detection, " in Proc. IEEE/CVF
Int. Conf. Comput. Vis. (ICCV), 2019, pp. 6568-6577.
[97] M. Kisantal, Z. Wojna, J. Murawski, J. Naruniec, and K. Cho,
" Augmentation for small object detection, " 2019. [Online].
Available: http://arxiv.org/abs/1902.07296
[98] S. Liu, L. Qi, H. Qin, J. Shi, and J. Jia, " Path aggregation network
for instance segmentation, " in Proc. IEEE Conf. Comput.
Vis. Pattern Recognit. (CVPR), 2018, pp. 8759-8768.
[99] C. Deng, M. Wang, L. Liu, and Y. Liu, " Extended feature pyramid
network for small object detection, " 2020. [Online]. Available:
https://arxiv.org/abs/2003.07021
[100] Q. Zhao et al., " M2Det: A single-shot object detector based
on multi-level feature pyramid network, " in Proc. 33rd AAAI
Conf. Artific. Intell., 2019, pp. 9259-9266. doi: 10.1609/aaai.
v33i01.33019259.
[101] Z. Liu, G. Gao, L. Sun, and Z. Fang, " HRDNet: High-resolution
detection network for small objects, " 2020. [Online]. Available:
https://arxiv.org/abs/2006.07607
[102] J. Noh, W. Bae, W. Lee, J. Seo, and G. Kim, " Better to follow, follow
to be better: Towards precise supervision of feature superresolution
for small object detection, " in Proc. IEEE/CVF Int.
Conf. Comput. Vis. (ICCV), 2019, pp. 9724-9733.
[103] J. Li, X. Liang, Y. Wei, T. Xu, J. Feng, and S. Yan, " Perceptual
generative adversarial networks for small object detection, " in
Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2017, pp.
1951-1959. doi: 10.1109/CVPR.2017.211.
[104] X. Yang et al., " SCRDet: Towards more robust detection for
small, cluttered and rotated objects, " in Proc. IEEE/CVF Int.
Conf. Comput. Vis. (ICCV), 2019, pp. 8231-8240. doi: 10.1109/
ICCV.2019.00832.
[105] J. Lim, M. Astrid, H. Yoon, and S. Lee, " Small object detection
using context and attention, " 2019. [Online]. Available: http://
arxiv.org/abs/1912.06319
[106] F. Yang, H. Fan, P. Chu, E. Blasch, and H. Ling, " Clustered object
detection in aerial images, " in Proc. IEEE/CVF Int. Conf.
Comput. Vis. (ICCV), 2019, pp. 8310-8319.
[107] V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman,
" A model for radar images and its application to adaptive
digital filtering of multiplicative noise, " IEEE Trans. Pattern
DECEMBER 2021 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
Anal. Mach. Intell., vol. PAMI-4, no. 2, pp. 157-166, 1982. doi:
10.1109/TPAMI.1982.4767223.
[108] D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, " Adaptive
noise smoothing filter for images with signal-dependent
noise, " IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-7, no.
2, pp. 165-177, 1985. doi: 10.1109/TPAMI.1985.4767641.
[109] L. I. Rudin, S. Osher, and E. Fatemi, " Nonlinear total variation
based noise removal algorithms, " Phys. D, Nonlinear Phenomena,
vol. 60, nos. 1-4, pp. 259-268, 1992. doi: 10.1016/01672789(92)90242-F.
[110]
C. R. Vogel and M. E. Oman, " Fast, robust total variationbased
reconstruction of noisy, blurred images, " IEEE Trans.
Image Process., vol. 7, no. 6, pp. 813-824, 1998. doi: 10.1109/
83.679423.
[111] J. Cai, H. Ji, C. Liu, and Z. Shen, " Framelet-based blind motion
deblurring from a single image, " IEEE Trans. Image Process., vol.
21, no. 2, pp. 562-572, 2012. doi: 10.1109/TIP.2011.2164413.
[112] M. Xu, M. R. Pickering, A. J. Plaza, and X. Jia, " Thin cloud
removal based on signal transmission principles and spectral
mixture analysis, " IEEE Trans. Geosci. Remote Sens.,
vol. 54, no. 3, pp. 1659-1669, 2016. doi: 10.1109/TGRS.2015.
2486780.
[113] Y. Zhang, B. Guindon, and J. Cihlar, " An image transform to
characterize and compensate for spatial variations in thin
cloud contamination of Landsat images, " Remote Sens. Environ.,
vol. 82, nos. 2-3, pp. 173-187, 2002. doi: 10.1016/S00344257(02)00034-2.
[114]
S. Le Hégarat-Mascle and C. André, " Use of Markov random
fields for automatic cloud/shadow detection on high resolution
optical images, " ISPRS J. Photogram. Remote Sens., vol.
64, no. 4, pp. 351-366, 2009. doi: 10.1016/j.isprsjprs.2008.
12.007.
[115] J. Zhang, M. K. Clayton, and P. A. Townsend, " Missing data
and regression models for spatial images, " IEEE Trans. Geosci.
Remote Sens., vol. 53, no. 3, pp. 1574-1582, 2015. doi: 10.1109/
TGRS.2014.2345513.
[116] C. Zeng, H. Shen, and L. Zhang, " Recovering missing pixels for
Landsat ETM + SLC-off imagery using multi-temporal regression
analysis and a regularization method, " Remote Sens. Environ.,
vol. 131, pp. 182-194, Apr. 2013. doi: 10.1016/j.rse.2012.
12.012.
[117] X. Li, H. Shen, L. Zhang, and H. Li, " Sparse-based reconstruction
of missing information in remote sensing images
from spectral/temporal complementary information, " ISPRS
J. Photogram. Remote Sens., vol. 106, pp. 1-15, Aug. 2015. doi:
10.1016/j.isprsjprs.2015.03.009.
[118] H. Li, L. Zhang, and H. Shen, " An adaptive nonlocal regularized
shadow removal method for aerial remote sensing images, "
IEEE Trans. Geosci. Remote Sens., vol. 52, no. 1, pp. 106-120,
2014. doi: 10.1109/TGRS.2012.2236562.
[119] G. D. Finlayson, S. D. Hordley, and M. S. Drew, " Removing
shadows from images using retinex, " in Proc. 10th Color Imag.
Conf., Color Sci. Eng. Syst., Technol., Appl., 2002, pp. 73-79.
[120] A. Suzuki, A. Shio, H. Arai, and S. Ohtsuka, " Dynamic shadow
compensation of aerial images based on color and spatial
analysis, " in Proc. 15th Int. Conf. Pattern Recognit. (ICPR'00),
31
http://www.arxiv.org/abs/1804.02767 http://www.arxiv.org/abs/1902.07296 https://www.arxiv.org/abs/2003.07021 https://www.arxiv.org/abs/2006.07607 http://www.arxiv.org/abs/1912.06319 http://www.arxiv.org/abs/1912.06319
IEEE Geoscience and Remote Sensing Magazine - December 2021

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - December 2021
