Evidence map›Paper›PMID 38078083›Full record

ArticleFrontiers in plant science2023

MSGF-GLP: fusion method of visible and hyperspectral data for early detection of discolored standing trees.

Hongwei Zhou, Yixuan Wu, Weiguang Wang, Jiayin Song, Guoyang Liu, Jie Shi, Hong Sun

Abstract read
In one paragraph

Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Hongwei ZhouCollege of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Yixuan WuCollege of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Weiguang WangSichuan Jiuzhou Electric Group CO., LTD, Mianyang, Sichuan, China.
Jiayin SongCollege of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Guoyang LiuCollege of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Jie ShiCollege of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Hong SunGeneral Station of Forest and Grassland Pest Management, National Forestry and Grassland Administration, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pest and disease damage to forests cannot be underestimated, so it is essential to detect diseased trees in time and take measures to stop their spread. The detection of discoloration standing trees is one of the important means to effectively control the spread of pests and diseases. In the visible wavelength range, early infected trees do not show significant color changes, which poses a challenge for early detection and is only suitable for monitoring middle and late discolor trees. The spectral resolution of hyperspectral restricts the improvement of its spatial resolution, and there are phenomena of different spectral of the same and foreign objects in the same spectrum, which affect the detection results. In this paper, the method of hyperspectral and CCD image fusion is used to achieve high-precision detection of discoloration standing trees. This paper proposes an improved algorithm MSGF-GLP, which uses multi-scale detail boosting and MTF filter to refine high-resolution data. By combining guided filtering with hyperspectral images, the spatial detail difference is enhanced, and the injection gain is interpolated into the difference of each band, so as to obtain high-resolution and high-quality hyperspectral images. This research is based on hyperspectral and CCD data obtained from LiCHy, Chinese Academy of Forestry, Maoershan Experimental Forest Farm, Shangzhi City, Heilongjiang Province. The evaluation framework is used to compare with the other five fusion algorithms to verify the good effect of the proposed method, which can effectively preserve the canopy spectrum and improve the spatial details. The fusion results of forestry remote sensing data were analyzed using the vegetation Normalized Difference Water Index and Plant Senescence Reflectance Index. The fused results can be used to distinguish the difference between discoloration trees and healthy trees by the multispectral vegetation index. The research results can provide good technical support for the practical application of forest remote sensing data fusion, and lay the foundation for promoting the scientific, automatic and intelligent forestry control.

Indexed as

data fusion methodsdata processingdiscolored standing treesforest remote sensinghyperspectral remote sensing

Identifiers

PMID38078083
PMCPMC10701741

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.