目标边缘保持约束的图像联合解卷积复原算法

发布时间：2018-03-26 14:09

本文选题：图像复原　切入点：边缘保持　出处：《测绘科学》2016年12期

【摘要】：针对图像复原过程中去噪与目标边缘特征保持之间的矛盾,该文提出了一种基于目标边缘保持的图像联合解卷积复原算法。首先,构建了一个目标边缘保持约束模型,实现对图像小梯度特征(噪声为主)的平滑、对图像大梯度特征(目标边缘为主)的保留,平衡复原处理过程中图像去噪与目标边缘保持之间的矛盾;然后,将目标边缘保持约束先验模型,引入MAP图像复原框架,提升MAP复原算法的可靠性和收敛性;最后,利用共轭梯度迭代优化计算过程,加快算法收敛速度。实验结果表明,该算法能较好地平衡图像去噪与目标边缘特征保持之间的矛盾,实现了图像高清晰复原。
[Abstract]:In view of the contradiction between denoising and edge feature preserving in image restoration, this paper proposes an image deconvolution algorithm based on object edge preservation. Firstly, a constraint model of object edge preserving is constructed. It can smooth image small gradient feature (noise mainly), preserve image large gradient feature (target edge), balance the contradiction between image denoising and object edge keeping in the process of restoration. The object edge preserving constraint priori model is introduced into the MAP image restoration framework to improve the reliability and convergence of the MAP restoration algorithm. Finally, the conjugate gradient iteration is used to optimize the calculation process to accelerate the convergence speed of the algorithm. The algorithm can balance the contradiction between image denoising and target edge feature preservation, and achieve high resolution image restoration.
【作者单位】：信息工程大学地理空间信息学院;空军空降兵学院;国家测绘地理信息局卫星测绘应用中心;北京大学工学院;
【基金】：广西自然科学基金项目(2012GXNSFAA053181,2013GXNSFBA019265,2013GXNSFBA019266) 测绘地理信息公益性行业科研专项(201512020)
【分类号】：TP391.41

【相似文献】