摘要
基于模糊数学的图像处理技术是图像处理中的重要技术。文中基于模糊熵的概念,提出了两种新的图像增强算法:一种是基于模糊熵的图像滤波器,另一种是改进的模糊松弛迭代增强算法。前者将图像分为若干窗口,分别计算每个窗口关于不同模糊集的模糊熵,根据最小模糊熵原则,确定该窗口中心灰度的大小,该方法充分利用了图像窗口中像素的区域信息;后者对图像依次进行模糊熵滤波去除噪声,最大模糊熵阈值确定分层和模糊隶属度松弛迭代增强,该方法能够实现对图像不同层次的内容实现可控式模糊增强,提高算法的自适应性并且能够增强算法的抗噪性能。通过与传统算法的实验结果对比,验证了文中算法能够取得较好的图像增强效果。
Image processing technique based on fuzzy mathematics is important in image processing technology. Based on the concept of fuzzy entropy, proposed two new image enhancement algorithms. One is the fuzzy entropy filtering. Another is improved fuzzy relaxation iterative image enhancement algorithm. The first method divides the image into several windows, calculating the fuzzy entropy of each window on different fuzzy sets. The method determines the value of the window center grayscale, according to the minimum fuzzy entropy principle, which makes full use of the area information of the pixels in the image window. In method two,use the fuzzy entropy filtering to remove noise, divide the image due to the maximum fuzzy entropy threshold and enhance the image through the fuzzy membership slack iterative algorithm. This method not only makes the controlled enhancement possible at the different levels of the image,but also im- proves self-adaptability and the anti-noise performance. Research indicates that the proposed algorithms can achieve better effect of image enhancement than traditional algorithms.
出处
《计算机技术与发展》
2013年第6期67-70,共4页
Computer Technology and Development
基金
国家自然科学基金资助项目(61070234)
关键词
图像增强
模糊熵滤波器
最大模糊熵
模糊松弛迭代
图像分层
image enhancement
fuzzy entropy filter
maximum fuzzy entropy
fuzzy relation iteration
image slicing
