计算机科学 ›› 2017, Vol. 44 ›› Issue (1): 295-299.doi: 10.11896/j.issn.1002-137X.2017.01.054
曹义亲,贺亚飞,黄晓生
CAO Yi-qin, HE Ya-fei and HUANG Xiao-sheng
摘要: 传统的基于压缩感知的图像融合算法是对整个系数进行稀疏处理,而小波分解后的低频系数不稀疏,导致压缩重构质量降低,并且传统的融合规则不易简单、全面地提取高频系数的特征值。针对这一问题,分别对小波分解得到的高、低频系数采取不同的融合规则进行处理,提出了一种改进的区域特性高频压缩感知的融合算法。其中,低频系数采用区域方差加权绝对值最大融合;高频系数首先通过具有较好RIP性质的随机观测矩阵进行压缩采样,得到的观测值基于能量匹配度的不同进行相加或加权融合,以融合不同方向的高频子带特征信息,再用正交匹配追踪重构算法对高频部分进行信号重构。最后,低频、高频信息在小波逆变换下重构出融合图像。实验结果表明,与以往的基于压缩感知的融合方法相比,此算法的融合图像更清晰,新算法无论是在主观评价还是客观评价指标上都有利于图像信号重构,并具有较好的使用性。
[1] PETROVI′ V,DIMITRIJEVI′ V.Focused pooling for imagefusion evaluation[J].Information Fusion,2015,22:119-126. [2] DONOHO D L.Compressed sensing[J].Information Theory,IEEE Transactions on Information Theory,2006,52(4):1289-1306. [3] WAN J,ZHOU S.Features extraction based on wavelet packet transform for B[C]∥ 2010 3rd International Congress on Image and Signal Processing (CISP).IEEE,2010:949-955. [4] ZHANG Yi-zhuo,MA Lin,XU Lei,et al.Wood board texture classification based on genetic fusion of wavelet and curvelet features[J].Journal of Beijing Forestry University,2014,6(2):119-124.(in Chinese) 张怡卓,马琳,许雷,等.基于小波与曲波遗传融合的木材纹理分类[J].北京林业大学学报,2014,36(2):119-124. [5] BAI X.Infrared and visual image fusion through feature extraction by morphological sequential toggle operator[J].Infrared Physics&Technology,2015,71:77-86. [6] LI Chao,ZHANG Yi-zhuo,YU Hui-ling,et al.Dualtree complex wavelet feature fusion and wood board collaborative detection by compressed Sensing[J].Electric Machines and Control,2015,9(8):81-87.(in Chinese) 李超,张怡卓,于慧伶,等.双树复小波特征融合的板材压缩感知协同检测与分选[J].电机与控制学报,2015,19(8):81-87. [7] YANG Y,DANG J,WANG Y.Medical image fusion method based on lifting wavelet transform and dual-channel PCNN[C]∥2014 IEEE 9th Conference on Industrial Electronics and Applications (ICIEA).IEEE,2014:1179-1182. [8] AFONSO S B,EDGAR D,DUSTIN G M,et al.Certifying the Restricted Isometry Property is Hard[J].Information Theory IEEE Transactions on,2013,59(6):3448-3450. [9] CANDS E J,TAO T.Decoding by Linear Programming[J].IEEE Transactions on Information Theory,2004,34(4):435-443. [10] CANDS E J,ROMBERG J K,TAO T.Stable signal recovery from incomplete and inaccurate measurements[J].Communications on Pure & AppliedMathematics,2006,59(8):1207-1223. [11] SAHOO S K,MAKUR A.Signal Recovery from Random Measurements via Extended Orthogonal Matching Pursuit[J].IEEE Transactions on Signal Processing,2015,63(10):2572-2581. [12] FU Ying-hua.Reconstruction of compressied sensing and semi-QR fact-orization[J].Journal of Compter Applications,2008,8(9):2300-2302.(in Chinese) 傅迎华.可压缩传感重构算法与近似QR分解[J].计算机应用,2008,8(9):2300-2302. [13] LUO X,ZHANG J,DAI Q.A regional image fusion based on similarity characteristics[J].Signal Processing,2012,92(5):1268-1280. [14] SHEN Xiao-hua,YANG Guo-sheng,ZHANG Huan-long.Im-proved on Approach of Image Fusin Based on Region-energy[J].Journal of Projectiles,Rockets,Missiles and Guidance,2006,6(4):279-281.(in Chinese) 申晓华,杨国胜,张焕龙.改进的基于区域能量的图像融合方法[J].弹簧与制导学报,2006,26(4):279-281. [15] XYDEAS C S,PETROVIC V.Objective image fusion perfor-mance measure[J].Electronics Letters,2000,6(4):308-309. |
No related articles found! |
|