Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from
the observed LR images. As SR has been developed for more than three decades, both …

Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …

In this paper, the development of pansharpening methods from traditional understanding to
the current understanding is comprehensively reviewed. Furthermore, the performance of …

摘要由于广泛的实用价值与理论价值, 超分辨率图像重建(Super-resolution image
reconstruction, SRIR 或SR) 技术成为计算机视觉与图像处理领域的一个研究热点 …

Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and
spectral resolutions. In this paper, we propose an integrated framework for the spatio …

The amount of noise included in a hyperspectral image limits its application and has a
negative impact on hyperspectral image classification, unmixing, target detection, and so on …

This paper presents a novel model for blending remote sensing data of high spatial
resolution (HSR), taken at infrequent intervals, with those available frequently but at low …

Super-resolution reconstruction proposes a fusion of several low-quality images into one
higher quality result with better optical resolution. Classic super-resolution techniques …

In hyperspectral remote sensing image classification, multiple features, eg, spectral, texture,
and shape features, are employed to represent pixels from different perspectives. It has …

Pansharpening aims to sharpen a lowspatial-resolution (LR) multispectral (MS) image using
a high-spatial-resolution (HR) panchromatic (Pan) image to obtain the HR MS image. It has …