Noisy Image Super-Resolution with Sparse Mixing Estimators

摘要：

Image super-resolution reconstruction (SR) has drawn a lot of attentions lately. But almost all existing SR algorithms do not consider about the noisy image SR problem. This paper proposes a novel superresolution algorithm for noisy images based on sparse mixing estimators. Firstly, sparse mixing estimators are introduced to achieve a directional and sparse representation of noisy low resolution (LR) image. Then, we employ the median filter to define thresholds using the local characters of the sparse representation. After the noise is removed by shrinkage thresholds, the adaptive interpolations are adopted to achieve high resolution (HR) image. Experimental results demonstrate that our algorithm shows satisfactory performance in noisy image superresolution reconstruction.

关键词： super-resolution sparse mixing estimators median filter shrinkage adaptive interplotation

作者: Fang Qiu Yi Xu Ci Wang Yuhong Yang

作者单位: Institute of Image Communication and Information Processing Department of Electronic Engineering, Shanghai Jiao Tong University Shanghai, P.R. China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1095-1099

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）