计算机科学 ›› 2020, Vol. 47 ›› Issue (9): 135-141.doi: 10.11896/jsjkx.190600146
田旭1, 常侃1,2,3, 黄升1, 覃团发1,2,3
TIAN Xu1, CHANG Kan1,2,3, HUANG Sheng1, QIN Tuan-fa1,2,3
摘要: 通过传统的单图像超分辨率(Super Resolution,SR)算法重建的高分辨率图像往往存在高频信息不足、边缘模糊的问题。为了提升重建图像的质量,提出了一种基于残差字典及协作表达的单图像SR算法(Residual Dictionary and Collaborative Representation,RDCR)。在训练环节,该算法结合字典学习及协作表达的思想,首先训练一个主字典及主投影矩阵,其次利用重建的样本图像训练多层残差字典及多层残差投影矩阵;在测试环节,通过逐层重建残差信息,得到不断精细化的高频信息,以提升重建的高分辨率图像的质量。通过实验证明,相比传统算法A+,所提算法在4倍上采样下的Set5及Set14图像集上可以分别获得0.20dB及0.18dB的峰值信噪比增益,在运算时间上所提算法与A+接近。
中图分类号:
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