基于模糊集的图像增强方法研究

Research and Implementation of Image Enhancement Based on Fussy Sets

图像增强处理中常用的均值滤波和中值滤波等方法有较强的抑制噪声的能力,在一定程度上会导致图像模糊,影响图像处理的效果。直方图均衡化是目前地震图像增强的主要方法,但它存在着图像细节信息丢失和噪声放大的缺点。基于模糊集的图像增强方法逐渐被应用到实际的图像处理中,并且显示出它优于传统图像增强算法的特点。因此,将基于模糊集的图像增强方法应用到图像处理中,以克服传统图像增强方法的不足。首先对传统的Pal-King基于模糊集的图像增强算法进行了研究。针对Pal-King算法的缺点和不足,提出了两种改进算法,并且运用模糊熵理论对改进算法的正确性进行了证明。

Mean filtering and median filtering methods,which are commonly used in image enhancement,have a stronger ability to suppress noise,but to some extent,it will blur the image processing and affect the interpretation results. Histogram equalization is the primary means of image enhancement,but there are some shortcomings of image detail information loss and noise amplification existing in it. The image enhancement based on fuzzy sets have been gradually applied to the actual image processing,and shown that it is superior to the traditional image enhancement algorithm. Consequently,applying image enhancement method based on fuzzy sets to the seismic image in order to overcome the deficiencies of traditional image enhancement methods is first proposed. Firstly,the traditional Pal-King image enhancement algorithm based on fuzzy sets has been studied. Two improved algorithms are proposed to overcome the shortcomings and deficiencies of the Pal-King algorithm,and the correctness of the improved algorithms is proved by fuzzy entropy theory.