南京大学学报(自然科学版) ›› 2019, Vol. 55 ›› Issue (4): 581591.doi: 10.13232/j.cnki.jnju.2019.04.008
所属专题: 测试专题
Weiqin Huang1,2(),Fengqiang Gao1,2,Junren Chen1,2,Chan Li1
摘要:
为了提高重建的质量和速度,提出一种联合深度置信网络与邻域回归的超分辨率算法.一方面,结合字典学习与神经网络表示的联系对传统的深度置信网络进行调整,采用该网络模型实现字典学习,充分利用该模型突出的学习能力,使字典具有更好的特征表达能力,从而提高图像的重建质量.另一方面,在基于字典学习的超分辨率框架中融入邻域回归思想.首先,利用最近邻域算法确定字典原子的最近邻域映射关系;然后以此为基础,结合邻域回归方法,离线计算高、低分辨率投影矩阵;最后在重建过程中将该投影矩阵应用于图像重建.该方法避免了字典学习中的系数求解过程,降低了计算的复杂度,提高了重建的速度.实验表明,算法具有更高的峰值信噪比和结构相似度,同时极大地提高了图像的重建速度.
中图分类号:
1 | 潘宗序,禹晶,肖创柏等. 基于自适应多字典学习的单幅图像超分辨率算法. 电子学报,2015,43(2):209-216. |
Pan Z X,Yu J,Xiao C B,et al.Single image super resolution based on adaptive multi?dictionary learning. Acta Electronica Sinica,2015,43(2):209-216. | |
2 | 苏衡,周杰,张志浩. 超分辨率图像重建方法综述. 自动化学报,2013,39(8):1202-1213. |
Su H,Zhou J,Zhang Z H.Survey of super?resolution image reconstruction methodsActa Automatica Sinica,2013,39(8):1202-1213.) | |
3 | FreemanW T,JonesT R,PasztorE C. Example?based super?resolution. Computer Graphics and Applications IEEE,2002,22(2):56-65. |
4 | YangJ C,WrightJ,HuangT,et al. Image super?resolution as sparse representation of raw image patches∥Proceedings of 2008 IEEE Conference on Computer Vision and Pattern Recognition. Anchorage,AK,USA:IEEE Press,2008:1-8. |
5 | ZeydeR,EladM,ProtterM. On single image scale?up using sparse?representations∥Proceeding of 7th International Conference on Curves and Surfaces. Springer Berlin Heidelberg,2010:24-30. |
6 | WoldS,EsbensenK,GeladiP. Principal component analysis. Chemometrics and Intelligent Laboratory Systems,1987,2(1-3):37-52. |
7 | TimofteR,DeV,Van GoolL. Anchored neighborhood regression for fast example?based super?resolution∥Proceedings of 2013 IEEE International Conference on Computer Vision. Sydney,Australia:IEEE,2013:1921-1927. |
8 | DongC,LoyC C,HeK M,et al. Image super?resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,38(2):295-307. |
9 | DonohoD L. For most large underdetermined systems of equations,the minimal 1?norm near?solution approximates the sparsest near?solution. Communications on Pure and Applied Mathematics,2006,59(7):907-934. |
10 | EnganK,AaseS O,HusoyJ H. Frame based signal compression using method of optimal directions (MOD)∥Proceedings of the 1999 IEEE International Symposium on Circuits and System. Orlando,FL,USA:IEEE,1999:1-4. |
11 | AharonM,EladM,BrucksteinA. K?SVD:an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing,2006,54(11):4311-4322. |
12 | KeyvanradM A,HomayounpourM M. A brief survey on deep belief networks and introducing a new object oriented toolbox (DeeBNet). 2014,arXiv:1408.3264. |
13 | SmolenskyP. Information processing in dynamical systems:foundations of harmony theory. Boston:MIT Press,1986,194-281. |
14 | KrizhevskyA. Learning multiple layers of features from tiny images. Master Dissertation. Toronto:University of Toronto,2009. |
15 | HintonG E,OsinderoS,TehY W. A fast learning algorithm for deep belief nets. Neural Computation,2014,18(7):1527-1554. |
16 | 蒋建国,陈亚运,齐美彬等. 基于自相似性和稀疏表示的图像超分辨率重建. 光电工程,2015,42(12):74-81. |
Jiang J G,Chen Y Y,Qi M B,et al.Image super?resolution reconstruction based on selfsimilarity and sparse representation. Opto?Electronic Engineering,2015,42(12):74-81. | |
17 | BevilacquaM,RoumyA,GuillemotC,et al. Low?complexity single image super?resolution based on nonnegative neighbor embedding∥Proceedings of British Machine Vision Conference. Guildford,British:BMVA Press,2012:1-10. |
18 | 李祚林,李晓辉,马灵玲等. 面向无参考图像的清晰度评价方法研究. 遥感技术与应用,2011,26(2):239-246. |
Li Z L,Li X H,Ma L L,et al.Research of definition assessment based on no?reference digital image quality. Remote Sensing Technology & Application,2011,26(2):239-246. | |
19 | 路鹤晴,朱国英,卓维海等. 医用X射线CT辐射剂量影响因素研究. 上海医学影像,2008,17(2):93-96,136. |
Lu H Q,Zhu G Y,Zhuo W H,et al.An evaluation on influence factors of radiation dose for the medical X?ray computed tomography. Shanghai Medical Imaging,2008,17(2):93-96,136. | |
20 | ClarkK,VendtB,SmithK,et al. The cancer imaging archive (TCIA):maintaining and operating a public information repository. Journal of Digital Imaging,2013,26(6):1045-1057. |
[1] | 罗鸣威2,王怀登1*,丁 尧1,袁 杰2. 变焦序列图像超分辨率重建算法研究[J]. 南京大学学报(自然科学版), 2017, 53(1): 165-. |
[2] | 王喆正, 唐 晔, 杨育彬 * . 利用图像类标信息的自调式字典学习方法 [J]. 南京大学学报(自然科学版), 2015, 51(2): 320-327. |
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