Remote Sensing Image Fusion Based on Adaptive IHS and Multiscale Guided Filter

被引:68
|
作者
Yang, Yong [1 ]
Wan, Weiguo [1 ]
Huang, Shuying [2 ]
Yuan, Feiniu [1 ]
Yang, Shouyuan [1 ]
Que, Yue [1 ]
机构
[1] Jiangxi Univ Finance & Econ, Sch Informat Technol, Nanchang 330032, Peoples R China
[2] Jiangxi Univ Finance & Econ, Sch Software & Commun Engn, Nanchang 330032, Peoples R China
来源
IEEE ACCESS | 2016年 / 4卷
基金
中国国家自然科学基金;
关键词
Image fusion; multispectral (MS) image; panchromatic (PAN) image; intensity-hue-saturation (IHS) transform; guided filter; PAN-SHARPENING METHOD; FRAMEWORK; QUALITY; MS;
D O I
10.1109/ACCESS.2016.2599403
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The purpose of remote sensing image fusion is to sharpen a low spatial resolution multispectral (MS) image by injecting the detail map extracted from a panchromatic (PAN) image. In this paper, a novel remote sensing image fusion method based on adaptive intensity-hue-saturation (IHS) and multiscale guided filter is presented. In the proposed method, the intensity component is obtained adaptively from the upsampled MS image at first. Different from traditional IHS-based methods, we subsequently propose a multiscale guided filter strategy to filter the PAN image to achieve more detail information. Finally, the total detail map is injected into each band of the upsampled MS image to obtain the fused image by a model-based algorithm, in which an improved injection gains approach is proposed to control the quantity of the injected detail information. Experimental results demonstrated that the proposed method can provide more spatial information and preserve more spectral information compared with several state-of-the-art fusion methods in both subjective and objective evaluations.
引用
收藏
页码:4573 / 4582
页数:10
相关论文
共 50 条
  • [41] An adaptive remote sensing image fusion algorithm based on Directionlet transform
    Bai, Jing
    Zhao, Baini
    Jiao, Lc
    MIPPR 2011: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS, 2011, 8006
  • [42] Multi-modal remote sensing image fusion method guided by local extremum maps-guided image filter
    Sun, Menghui
    Zhu, Xiaoliang
    Niu, Yunzhen
    Li, Yang
    SIGNAL IMAGE AND VIDEO PROCESSING, 2024, 18 (05) : 4375 - 4383
  • [43] An improved adaptive filter for remote sensing image denoising
    Huang, Rui
    Liu, Hui
    Dong, Zhi
    Jiang, Ziyang
    PROCEEDINGS OF THE IAMG '07: GEOMATHEMATICS AND GIS ANALYSIS OF RESOURCES, ENVIRONMENT AND HAZARDS, 2007, : 458 - +
  • [44] Remote sensing image fusion based on morphological filter and convolutional sparse representation
    Liu Yuting
    Liu Fan
    INTERNATIONAL CONFERENCE ON SENSORS AND INSTRUMENTS (ICSI 2021), 2021, 11887
  • [45] A ViT-Based Multiscale Feature Fusion Approach for Remote Sensing Image Segmentation
    Wang, Wei
    Tang, Chen
    Wang, Xin
    Zheng, Bin
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [46] A CBAM Based Multiscale Transformer Fusion Approach for Remote Sensing Image Change Detection
    Wang, Wei
    Tan, Xinai
    Zhang, Peng
    Wang, Xin
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2022, 15 : 6817 - 6825
  • [47] Remote Sensing Image Change Detection Based on Lightweight Transformer and Multiscale Feature Fusion
    Li, Jingming
    Zheng, Panpan
    Wang, Liejun
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2025, 18 : 5460 - 5473
  • [48] Adaptive regularized scheme for remote sensing image fusion
    Sizhang TANG
    Chaomin SHEN
    Guixu ZHANG
    Frontiers of Earth Science, 2016, 10 (02) : 236 - 244
  • [49] An Improved Adaptive IHS Method for Image Fusion
    Wang, Ting
    SEVENTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2015), 2015, 9817
  • [50] Adaptive regularized scheme for remote sensing image fusion
    Sizhang Tang
    Chaomin Shen
    Guixu Zhang
    Frontiers of Earth Science, 2016, 10 : 236 - 244