Next Article in Journal
Object-Based Window Strategy in Thermal Sharpening
Next Article in Special Issue
A Local Feature Descriptor Based on Oriented Structure Maps with Guided Filtering for Multispectral Remote Sensing Image Matching
Previous Article in Journal
A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization
Previous Article in Special Issue
Enhancement of Component Images of Multispectral Data by Denoising with Reference
Open AccessArticle

Pansharpening Using Guided Filtering to Improve the Spatial Clarity of VHR Satellite Imagery

1
Department of Civil Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, Korea
2
Korea Aerospace Research Institute, Gwahak-ro, Yuseong-Gu, Daejeon 34133, Korea
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(6), 633; https://doi.org/10.3390/rs11060633
Received: 18 February 2019 / Revised: 10 March 2019 / Accepted: 12 March 2019 / Published: 15 March 2019
(This article belongs to the Special Issue Multispectral Image Acquisition, Processing and Analysis)
Pansharpening algorithms are designed to enhance the spatial resolution of multispectral images using panchromatic images with high spatial resolutions. Panchromatic and multispectral images acquired from very high resolution (VHR) satellite sensors used as input data in the pansharpening process are characterized by spatial dissimilarities due to differences in their spectral/spatial characteristics and time lags between panchromatic and multispectral sensors. In this manuscript, a new pansharpening framework is proposed to improve the spatial clarity of VHR satellite imagery. This algorithm aims to remove the spatial dissimilarity between panchromatic and multispectral images using guided filtering (GF) and to generate the optimal local injection gains for pansharpening. First, we generate optimal multispectral images with spatial characteristics similar to those of panchromatic images using GF. Then, multiresolution analysis (MRA)-based pansharpening is applied using normalized difference vegetation index (NDVI)-based optimal injection gains and spatial details obtained through GF. The algorithm is applied to Korea multipurpose satellite (KOMPSAT)-3/3A satellite sensor data, and the experimental results show that the pansharpened images obtained with the proposed algorithm exhibit a superior spatial quality and preserve spectral information better than those based on existing algorithms. View Full-Text
Keywords: KOMPSAT-3A; pansharpening; guided filtering (GF); spatial clarity; optimal injection gains; spatial dissimilarity KOMPSAT-3A; pansharpening; guided filtering (GF); spatial clarity; optimal injection gains; spatial dissimilarity
Show Figures

Figure 1

MDPI and ACS Style

Choi, J.; Park, H.; Seo, D. Pansharpening Using Guided Filtering to Improve the Spatial Clarity of VHR Satellite Imagery. Remote Sens. 2019, 11, 633.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop