计算机工程Issue(2)：233-236,4.DOI:10.3969/j.issn.1000-3428.2014.02.050
基于Curvelet变换的图像压缩感知重构
Image Compressed Sensing Reconstruction Based on Curvelet Transform
摘要
Abstract
Discrete Cosine Transform(DCT) and wavelet transform are used for sparse representation, but DCT can’t analyse well in domain of time and frequency. The directional selectivity of wavelet transform is poor and can’t reconstruct edge information well enough. Against the optimization of sparse representation, Curvelet transform has characters of multi-scale, singularity and more sparsity. This paper proposes a compressed sensing reconstruction algorithm based on Curvelet transform, which uses Curvelet transform for sparse representation and thresholding method in wavelet domain to solve the noise problem of signal reconstruction. Results demonstrate that the algorithm gets 1.86 dB higher Peak Signal to Noise Ratio(PSNR) and 1.15 dB higher PSNR compared with traditional wavelet transform and Contourlet transform. As Curvelet transform is applied to compressed sensing, optimal result of edge and smooth part of image are got, also the reconstructed quality of details is increased.关键词
图像处理/压缩感知/稀疏表示/阈值处理/信号重构/Curvelet 变换Key words
image processing/compressed sensing/sparse representation/threshold processing/signal reconstruction/Curvelet transform分类
信息技术与安全科学引用本文复制引用
叶慧,孔繁锵..基于Curvelet变换的图像压缩感知重构[J].计算机工程,2014,(2):233-236,4.基金项目
国家自然科学青年基金资助项目(61102069)；江苏省自然科学基金资助面上项目(BK2010498)；博士后科学基金资助项目(20110491421)；南京航空航天大学青年科技创新基金资助项目(NS2012027, NS2013085)；南京航空航天大学基本科研业务费专项科研基金资助项目(NP2011048) （61102069）
