基于变分贝叶斯的视觉散焦光图像快速盲复原算法  

Fast Blind Restoration Algorithm of Visual Defocus Image Based on Variable Bayesian

作　　者：姜新军 JIANG Xinjun(Department of Technical,Taiyuan Satellite Launch Center,Taiyuan 030000,China)

机构地区：[1]太原卫星发射中心技术部,太原030000

出　　处：《吉林大学学报（信息科学版）》2023年第3期552-558,共7页Journal of Jilin University（Information Science Edition）

基　　金：山西省自然科学基金资助项目(201901D111061)。

摘　　要：为实现数字图像的高精度应用,降低外界光线对视觉成像的影响,提出一种基于变分贝叶斯的视觉散焦光图像快速盲复原算法。通过梯度和卷积处理,计算视觉散焦光图像后验概率期望,利用Sobolev空间函数分布方法提取最优初始图像和散焦光模糊函数先验概率。以变分贝叶斯的近似分布思想,无限逼近实际的后验概率;使用相对熵计算多个分布间距离,最大程度贴近真实值;将最小损耗代价函数输入双边滤波器内,即以近似清晰图像为指导图,剔除剩余高频噪声,得到最优图像盲复原结果。实验结果表明,所提算法盲复原后图像对比度高,边缘细节清晰,复原速度快,具有极高的应用价值。In order to realize the high-precision application of digital images and reduce the influence of external light on visual imaging,a fast blind restoration algorithm for visual defocused light images based on variational Bayesian is proposed.Through gradient and convolution processing,the posterior probability expectation of the visual defocused light image is calculated,and the optimal initial image and the prior probability of the defocused light blur function are extracted by using the Sobolev space function distribution method.The actual posterior probability is reached infinitely,using relative entropy to calculate the distance between multiple distributions,to approximate the true value of the greatest extent,and input the minimum loss cost function into the bilateral filter,that is,take the approximate clear image as the guide map,to remove the remaining high-frequency noise.The optimal image blind restoration results are obtained.The experimental results show that the proposed algorithm has high image contrast,clear edge details and fast restoration speed after blind restoration,which has extremely high application value.

关 键 词：最小损耗代价函数 变分贝叶斯 散焦光图像 后验概率 相对熵 双边滤波器 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]