CAJ | 학술논문

为了拓展压缩传感(CS)的应用潜力,提出一种结合双树轮廓波(DT-Contourlet)及CS的多聚焦图像融合方法.该方法首先采用DT-Contourlet对源图像进行分解,提取图像的多尺度信息及方向信息,克服传统轮廓波变换不具平移不变性的缺点.接着,在DT-Contourlet域,将分解系数看成包含稠密和稀疏两部分:对稠密成份,根据散焦的表现形式,采用邻域梯度作为清晰度指标,用选择法实现融合处理;对稀疏成份,则在CS框架下,通过少数线性测量的融合,依据L1范数最小化,采用两步迭代收缩的重构算法,得到融合结果.实验表明,该方法重构时收敛速度比正交匹配追踪法快,且融合结果无论在视觉质量及定量指标上都明显优于传统方法.
위료탁전압축전감(CS)적응용잠력,제출일충결합쌍수륜곽파(DT-Contourlet)급CS적다취초도상융합방법.해방법수선채용DT-Contourlet대원도상진행분해,제취도상적다척도신식급방향신식,극복전통륜곽파변환불구평이불변성적결점.접착,재DT-Contourlet역,장분해계수간성포함주밀화희소량부분:대주밀성빈,근거산초적표현형식,채용린역제도작위청석도지표,용선택법실현융합처리;대희소성빈,칙재CS광가하,통과소수선성측량적융합,의거L1범수최소화,채용량보질대수축적중구산법,득도융합결과.실험표명,해방법중구시수렴속도비정교필배추종법쾌,차융합결과무론재시각질량급정량지표상도명현우우전통방법.
In order to expand the capability of Compressed Sensing(CS),a fusion method for multi-focus image using Dual-tree Contourlet(DT-Contourlet)and CS is proposed.First,the source images are decomposed using DT-Contourlet for extracting multiscale and direction information while overcoming the limitation of traditional contourlet which is lack of shift invariance.Then,in DT-Contourlet domain,the decomposition coefficients are treated as containing two components,i.e.,dense and sparse components.The dense components are fused using selection method by introducing neighborhood gradient as clarity index to indicate the characteristics of defocus.The sparse components are fused under the framework of CS via fussing a few linear measurements by solving the problem of L1 norm minimization which is based on a two-step iterative shrinkage/threshold reconstruction algorithm.The experiments demonstrate that the convergence rate of reconstruction is faster than that of orthogonal matching pursuit.Meanwhile,the proposed method provides more satisfactory fusion results in terms of visual quality and quantitative criterion.