摘要
Russo提出了一种模糊图像增强方法,该方法的效果由一个事先给定的参数来控制,由于同一幅图像不同区域的灰度值分布不尽相同,所以固定的参数并不能取得满意效果。为了获得更好的滤噪效果,研究了一种基于图像区域信息的改进的自适应模糊图像增强方法。该方法首先计算每个像素与其邻域像素的平均灰度差,然后根据该差值为每个像素分配一个噪声率,最后通过该噪声率来自适应地选择参数。该方法能够在滤除图像噪声的同时,不损失图像的细节特征信息。实验结果显示该方法较原方法有较大改进,并明显优于其他一些常规方法。
An effective fuzzy method for image enhancement was presented by Russo, in which the effectiveness was controlled by a given parameter. That method was far from being satisfied since the gray values in different image areas were varied while the parameter were fixed. For better noise filtering effectiveness, an improved method of adaptive fuzzy image enhancement is presented by this paper, which sets the parameters through the area-specific information. This improved method first calculates the difference between gray values of every pixel and the average of its neighborhood. Based on which noise rate was allotted to every pixel. The parameter was finally obtained adaptively by means of the noise rate. This method was proved effective in image noise filtering while losing no detailed image information. An experimental study showed that this method, much improved in comparison with Russo＇s method, was superior to any other commonly adopted ones.
出处
《中国图象图形学报》
CSCD
北大核心
2007年第8期1339-1343,共5页
Journal of Image and Graphics
关键词
模糊图像增强
平滑
锐化
噪声滤除
自适应
Fuzzy image enhancement, smoothing, sharpening, noise filtering, adaptive
