Image super-resolution is essential for a variety of applications such as medical imaging,surveillance imaging,and satellite imaging,among others.Traditionally,the most popular color image super-resolution is performe...Image super-resolution is essential for a variety of applications such as medical imaging,surveillance imaging,and satellite imaging,among others.Traditionally,the most popular color image super-resolution is performed in each color channel independently.In this paper,we show that the super-resolution quality can be further enhanced by exploiting the cross-channel correlation.Inspired by the High-Quality Linear Interpolation(HQLI)demosaicking algorithm by Malvar et al.,we design an image super-resolution scheme that integrates intra-channel interpolation with cross-channel details by isotropic linear combinations.Despite its simplicity,our super-resolution method achieves the accuracy comparable with the existing fastest state-of-the-art super-resolution algorithm at 20 times faster speed.It is well applicable to applications that adopt traditional interpolations,for improved visual quality at trivial computation cost.Our comparative study verifies the effectiveness and efficiency of the proposed super-resolution algorithm.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.61472157 and 61872162the Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University,under Grant No.VRLAB2020C05.
文摘Image super-resolution is essential for a variety of applications such as medical imaging,surveillance imaging,and satellite imaging,among others.Traditionally,the most popular color image super-resolution is performed in each color channel independently.In this paper,we show that the super-resolution quality can be further enhanced by exploiting the cross-channel correlation.Inspired by the High-Quality Linear Interpolation(HQLI)demosaicking algorithm by Malvar et al.,we design an image super-resolution scheme that integrates intra-channel interpolation with cross-channel details by isotropic linear combinations.Despite its simplicity,our super-resolution method achieves the accuracy comparable with the existing fastest state-of-the-art super-resolution algorithm at 20 times faster speed.It is well applicable to applications that adopt traditional interpolations,for improved visual quality at trivial computation cost.Our comparative study verifies the effectiveness and efficiency of the proposed super-resolution algorithm.
