Super-resolution algorithm using noise level adaptive dictionary

Shin-Cheol Jeong, Y. Kang, B. Song
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引用次数: 2

Abstract

This paper presents a noise-robust super-resolution algorithm. In learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in the inference phase. Experimental results show that the proposed algorithm outperforms the existing algorithms even for noisy images.
基于噪声级自适应字典的超分辨率算法
提出了一种抗噪声的超分辨算法。在学习阶段,根据噪声级别构建分类字典,然后在推理阶段使用字典合成高分辨率图像。实验结果表明,即使在有噪声的图像中,该算法也优于现有算法。
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