摘要
提出一种基于能量约束的自适应加权图像盲复原算法。首先,将图像划分成多幅子图像,引入图像梯度作为权重构建加权光学传递函数估计模型,以减少图像纹理对光学传递函数辨识的影响;其次,根据图像信号能量建立约束方程,采用二分法选择最优复原结果,实现自适应图像盲复原。仿真实验和多光谱遥感图像实验结果都表明,该算法具有较高的峰值信噪比和结构相似度,能有效恢复高斯类模糊图像,增强图像细节分辨能力,提高图像的主观视觉效果。该算法可应用于数据量大、实时性强的领域。
An adaptively-weighted blind image restoration algorithm based on energy constraint is proposed.The images are divided into several sub-images and gradients of sub-images are introduced as weights to build the estimation model of weighted optical transfer function,which can reduce the influence of image texture on the estimation of optical transfer function.Based on the energy of image signals,the constraint equation is established,and the optimal restoration result is chosen by the dichotomy to realize adaptive blind image restoration.Results of simulation and multispectral remote sensing image experiments show that the proposed algorithm can produce high peak signal-to-noise ratio and structural similarity,which will effectively restore Gaussian blurred images,enhance the image resolution,and improve subjective visual effects.The proposed algorithm can be applied to the fields requiring large data and real-time monitoring.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2018年第2期104-111,共8页
Acta Optica Sinica
基金
吉林省科技发展计划资助(20170204029GX)
关键词
图像处理
光学传递函数
图像复原
图像信号能量
image processing
optical transfer function
image restoration
image signal energy
