In the learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in ...

Jeong and Song: Noise-robust superresolution based on a classified dictionary. Input LR image. Extraction of. LR and HR patches. Dictionary construction.

A noise-robust superresolution algorithm that overcomes the problem of noise components existing in input images due to the mismatch between noise-free ...

In the learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in ...

This paper presents a noise-robust super-resolution algorithm. In learning phase, a dictionary classified according to noise level is constructed, ...

In this paper, a single-computed tomography (CT) image super-resolution (SR) reconstruction scheme is proposed. This SR reconstruction scheme is based on ...

N2 - this paper presents a noise-robust super-resolution algorithm. In learning phase, a dictionary classified according to noise level is constructed, and then ...

The position-patch and dictionary-based face super-resolution model is introduced to generate a high-resolution image from outlier infected low-resolution image ...

The problem of super resolution of noisy single LR observation is addressed in this paper. A neighbor embedding based method is proposed using denoised patch ...

Results demonstrate that our proposed algorithm performs superior image reconstructions that are almost noise-free. Our proposed method also performed better ...