计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (7): 181-183.DOI: 10.3778/j.issn.1002-8331.2009.07.054

• 图形、图像、模式识别 • 上一篇    下一篇

基于图像子块加权缩小的自适应修正算法

常 军,吴锡生   

  1. 江南大学 信息工程学院,江苏 无锡 214122
  • 收稿日期:2008-01-21 修回日期:2008-04-28 出版日期:2009-03-01 发布日期:2009-03-01
  • 通讯作者: 常 军

Self-adaptive amending algorithm of image zooming-out based on weighted averaging image sub-block

CHANG Jun,WU Xi-sheng   

  1. School of Information Technology,Jiangnan University,Wuxi,Jiangsu 214122,China
  • Received:2008-01-21 Revised:2008-04-28 Online:2009-03-01 Published:2009-03-01
  • Contact: CHANG Jun

摘要: 提出了一种基于图像子块加权缩小的自适应修正算法,有效地保持了灰度图像信息的完整性。首先,通过对加权平均缩小后得到的低分辨率图像进行对比拉伸处理,然后根据局部区域方差对整体图像的影响情况,对缩小图像像素点进行自适应修正。实验证明,算法克服了加权平均缩小后图像的边缘锯齿和模糊效应,使修正优化后的图像清晰。尤其对缩小比率大的图像质量的提高有较显著的效果。

关键词: 图像缩小, 自适应, 局部区域方差, 加权平均, 均值滤波器

Abstract: A self-adaptive amending algorithm of image zooming-out based on weighted averaging image sub-block is presented in this paper.This algorithm effectively retains the integrity of gray image information.First,low-resolution image obtained by weighted averaging for image zooming-out is disposed by the way of contrast extension .Then the algorithm takes account of the influence on the whole image information by local area variance and self-adaptively amends the every pixel value of low-resolution image.Experimental results demonstrate that the algorithm can more effectively avoid blurring and artifacts edges than only by the method of weighted averaging for image zooming-out,and generate high quality images.Especially,the visual quality of the images for the large ratio of image zooming-out is more prominent.

Key words: image zooming-out, self-adaptive, local area variance, weighted average, average value filter