Single image super-resolution (SISR) is an important research field in computer vision, the
purpose of which is to recover clear, high-resolution (HR) images from low-resolution (LR) …

Backlit image enhancement is a crucial task in improving the quality and visibility of the
underexposed regions in an image caused by the difference in illumination between the …

This study aims to tackle the challenge of detecting pedestrians in low-resolution (LR)
images by using super-resolution techniques. The proposed Wavelet Structure-Texture …

Super-resolution (SR) methods have significantly contributed to the improvement of the
spatial resolution of remote sensing (RS) images. The development of deep learning …

Convolutional neural networks can automatically learn features via deep network
architectures and given input samples. However, robustness of obtained models may have …

The degradation of visual quality in remote sensing images caused by haze presents
significant challenges in interpreting and extracting essential information. To effectively …

Stereoscopic omnidirectional images (SODIs) usually require recording very high-resolution
(HR) information whereby it is beneficial to exploit a super-resolution (SR) scheme to super …

Despite the fact that there is a remarkable achievement on multifocus image fusion, most of
the existing methods only generate a low-resolution image if the given source images suffer …

The color information are the most commonly used prior knowledge for depth map super-
resolution (DSR), which can provide high-frequency boundary guidance for detail …

The imaging system of visual measurement equipment is usually affected by environment
factors, such as distortion, blurring, and noise, which lead to the degradation of the acquired …