摘要
图像复原是图像处理中一个重要的研究课题。大部分图像复原算法,都只是单纯地利用图像灰度或梯度信息,并没有考虑图像的空间结构信息。Roth等人提出的专家场模型,采用固定的,通过学习得到的滤波器,虽然能充分地表现图像空间结构信息,但它不具有自适应特性。提出了一个空间结构自适应的专家场模型,它能够依据图像的结构信息自适应地调整所使用的滤波器。主要利用图像边缘方向来设计专家场模型中的滤波器,能够依据边缘方向自适应调整。在图像去噪中使用这个新的专家场模型,能够自适应地根据图像空间结构信息,实施不同程度的复原处理。实验结果分析表明,新专家场模型改善了图像复原质量,它的性能也优于传统的专家场模型。
Image restoration is an important research subject in image processing.Image gray or gradient magnitude is used in most of image restoration algorithm and spatial information is not adopted.A Field of Experts（FoEs） model which Roth et al presented adopts some fixed filters by learning.These filters can throughly characterize image spatial information,but it is not adaptive.In this paper,a spatially adaptive FoEs model is presented,which can adaptively adjust own filters to image spatial information.In FoEs model,filters are designed according to image edge direction and can be adaptively adjusted.When the new FoEs model is used for image denoising,varying restoration processing is adopted according to image spatial information.The results show that the new FoEs model significantly improves the image restoration quality and its performance is over traditional FoEs model’s.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第3期179-182,共4页
Computer Engineering and Applications
关键词
图像复原
图像去噪
空间结构
自适应
专家场
image restoration
image denoising
spatially structure
adaptive
field of expert
