摘要
双边滤波能在去除噪声的同时有效地保留图像的边缘信息。但双边滤波的时间复杂度高,执行时间长。根据近似层和亮度分层的概念,利用标识点及像素层来快速实现双边滤波。首先根据灰度差值划分图像的像素层,然后在像素层上选择标识点,并利用标识点计算像素层的滤波值,最后通过线性插值获得各像素点的滤波值,并输出滤波图像。该改进算法称为标识点双边滤波(Identification Bilateral Filtering)。在实验中分别对灰度和彩色图像进行了双边滤波。实验结果表明,IBF算法执行时间短,并能获得较好的滤波效果。
Bilateral filtering is a technique to delete images noise while effectively preserving edges. The na＇fve imple- mentation of the bilateral filtering can be extremely slow. The time complexity is high. According to concepts of appro- ximate layer and intensity layer, a improved bilateral filtering was proposed. This improved algorithm uses identification and pixel layer to realize Bilateral Filtering. This improved algorithm is called identification Bilateral Filtering（IBF）. At first, the pixel layer with gray D-value was specified, then identification point in pixel layer was choosen, and the filte- ring value of every pixel layers with identification point was computed. At last, linear interpolation was used to compute filtering value of pixels and output filtered image. Gray image and color image were taken as research objects in experi- ment. Experiment results show that the IBF algorithm has short executing time and has a good filtering result.
出处
《计算机科学》
CSCD
北大核心
2013年第7期262-265,共4页
Computer Science
基金
国家自然科学基金项目(61104179)
山东省教育厅资助项目(J11LG02
J10LG67)
聊城大学自然科学基金(X09031)
山东省高校智能信息处理与网络安全重点实验室项目资助
关键词
双边滤波
像素层
标识点
欧氏距离
Bilateral filtering, Pixel layer, Identification point, Euclidean distance
