Superresolution of Single Gaofen-4 Visible-Light and Near-Infrared (VNIR) Image Based on Texture Image Extraction
Superresolution of Single Gaofen-4 Visible-Light and Near-Infrared (VNIR) Image Based on Texture Image Extraction
复制标题
基于纹理图像提取的单张高分四号可见光和近红外（VNIR）图像超分辨率
DOI：
10.1109/jstars.2019.2926490
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发表时间：
2019-07
影响因子：
5.5
通讯作者：
Yufeng Cheng
中科院分区：
文献类型：
--
作者：
Mi Wang;Luxiao He;Xueli Chang;Yufeng Cheng
Superresolution (SR) is an important compensatory mean for geostationary orbit (GEO) satellites because of their low spatial resolution caused by orbital height. The multiple-image SR (MISR) methods generally have better reconstruction effects than single-image SR (SISR) methods. However, MISR methods require multiple images of the same place, which are susceptible to geometric distortion and radiation differences. Gaofen-4 (GF-4) is a GEO satellite equipped with a visible-light and near-infrared (VNIR) sensor and provides images with five bands. Based on the similarity of spatial information between different bands, this paper proposes an SISR method suitable for GF-4 VNIR images. The radiation differences are eliminated by extracting texture images. The high-resolution (HR) texture image is reconstructed by projections onto convex sets. The final SR result is fused by HR texture image and upsampled VNIR image. Tested by real GF-4 data, the reconstructed results of this method have better sharpness and more abundant information than comparable methods.
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