Title:
TWO-ORDER LIGHTWEIGHT NETWORK PANCHROMATIC SHARPENING METHOD COMBINING GUIDED FILTERING AND NSCT
Document Type and Number:
WIPO Patent Application WO/2023/000505
Kind Code:
A1
Abstract:
Provided in the present invention is a two-order lightweight network panchromatic sharpening method combining guided filtering and NSCT. The advantage of retaining better edge and detail information by guided filtering and the advantage of multi-scale multi-directional decomposition of NSCT are combined with a CNN, so as to construct a two-order lightweight network model to fuse an MS image and a PAN image, wherein by means of guided filtering, the panchromatic image MLPAN, which has been subjected to histogram matching, is filtered, so as to obtain a multi-scale high-frequency component and low-frequency component; by means of NSCT, an I-component image extracted from the MS image is filtered, so as to obtain a multi-scale multi-directional high-frequency directional sub-band image and low-frequency sub-band image; a detail extraction network ResCNN is constructed by using the advantage of a residual module, so as to extract in-details; and finally, a nonlinear model NLCNN is constructed by means of taking the in-details and a DUMS image as inputs, and the NLCNN is fully trained to obtain an optimal model. By means of the method, spectral information is retained while spatial resolution can be increased to a greater extent, the network structure is simple, the training time is reduced, an over-fitting phenomenon is prevented from occuring, and the fusion performance is improved.
Inventors:
HUANG MENGXING (CN)
WU YUANYUAN (CN)
LI YUCHUN (CN)
FENG SILING (CN)
WU YUANYUAN (CN)
WU DI (CN)
WU YUANYUAN (CN)
LI YUCHUN (CN)
FENG SILING (CN)
WU YUANYUAN (CN)
WU DI (CN)
Application Number:
PCT/CN2021/122464
Publication Date:
January 26, 2023
Filing Date:
September 30, 2021
Export Citation:
Assignee:
UNIV HAINAN (CN)
International Classes:
G06N3/04; G06T5/40; G06T3/40
Foreign References:
| CN110660038A | 2020-01-07 | |||
| US20200265597A1 | 2020-08-20 |
Other References:
YANG YONG, LU HANGYUAN; HUANG SHUYING; TU WEI; LI LUYI: "Remote Sensing Image Fusion Method Based on Adaptive Injection Model", JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS, GAI KAN BIAN WEI HUI, BEIJING, CN, vol. 45, no. 12, 31 December 2019 (2019-12-31), CN , pages 2351 - 2363, XP093026726, ISSN: 1001-5965, DOI: 10.13700/j.bh.1001-5965.2019.0372
HU JIANWEN; HU PEI; KANG XUDONG; ZHANG HUI; FAN SHAOSHENG: "Pan-Sharpening via Multiscale Dynamic Convolutional Neural Network", IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, IEEE, USA, vol. 59, no. 3, 16 July 2020 (2020-07-16), USA, pages 2231 - 2244, XP011838586, ISSN: 0196-2892, DOI: 10.1109/TGRS.2020.3007884
IMANI, M.: "Band Dependent Spatial Details Injection Based on Collaborative Representation for Pansharpening", IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, vol. 11, no. 12, 31 December 2018 (2018-12-31), XP011695716, DOI: 10.1109/JSTARS.2018.2851791
HU JIANWEN; HU PEI; KANG XUDONG; ZHANG HUI; FAN SHAOSHENG: "Pan-Sharpening via Multiscale Dynamic Convolutional Neural Network", IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, IEEE, USA, vol. 59, no. 3, 16 July 2020 (2020-07-16), USA, pages 2231 - 2244, XP011838586, ISSN: 0196-2892, DOI: 10.1109/TGRS.2020.3007884
IMANI, M.: "Band Dependent Spatial Details Injection Based on Collaborative Representation for Pansharpening", IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, vol. 11, no. 12, 31 December 2018 (2018-12-31), XP011695716, DOI: 10.1109/JSTARS.2018.2851791
Attorney, Agent or Firm:
HAINAN HEIP INTELLECTUAL PROPERTY AGENCY CO.LTD (CN)
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