摘要
针对被脉冲噪声污染的观测图像提出了一种基于自相似灰度校正的自适应图像复原算法.该算法首先用有选择的中值滤波器对脉冲噪声进行抑制,然后利用图像的自相似性对像素值进行校正以克服中值滤波器造成的图像局部区域像素相关性增加对图像复原处理产生的不利影响.用规整化方法进行图像复原处理,并且使用在灰度校正过程中得到的竞争因子对图像局部区域的统计量进行加权来产生规整化参数,并使其在迭代过程中自适应的更新.实验结果表明,该算法获得的复原图像具有良好的客观评价指标和主观视觉效果.
In this paper, an image restoration algorithm that is based on the self-similarity gray value adjustment method is proposed for the images contaminated by impulse noise. In the preliminary phase, a selective median filter is used to detect and suppress impulse noise. Then a gray value adjustment method based on self-similarity is employed for eliminating the pixels relativity that is produeed by the median filter. This algorithm uses an adaptive regularization method to restore the images. The regularization parameters are adaptively obtained through both the statistical parameters of image local region and the competition factors that are produced during the gray value adjustment procedure. The experimental results show that the restored images that are obtained by the proposed algorithm have better objective quality and subjective vision effect than that by some conventional methods for images contaminated by impulse noise.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2006年第11期1939-1946,共8页
Journal of Computer Research and Development
关键词
图像复原
中值滤波器
自相似
脉冲噪声
image restoration
median filter
self similarity
impulse noise
