【摘要】 针对传统的图像模糊增强算法增强强度小、处理灰度层次变化丰富的图像效果不佳以及控制参量难以设置等问题,提出了一种新的图像模糊增强算法.首先对局部窗口中像素点进行基于邻域一致性模糊熵测度的分类,并以分类为依据,对每个像素点均确定一最佳渡越点.对模糊隶属度函数也进行了研究改进,设计的函数具有良好的曲线形状,并通过调整控制参量,使渡越点的位置和函数曲线进行最佳的结合,能通过少量的迭代次数获得较好的增强效果.在模糊逆映射上,采用线性逆变换函数,保持了模糊映射所带来的增强效果,并消除了由于截断带来的灰度信息的损失,在运算效率上也得到了提高.新算法对灰度变化丰富的路面图像的增强取得了良好的效果,并且控制参量均为自适应计算,不需进行人为干预,具有很好的通用性.更多还原

【Abstract】 Compared with traditional fuzzy image enhancement algorithms,which can not enhance images with changeful grey levels well and is difficult to decide the control parameters,a new fuzzy image enhancement algorithm is proposed to overcome the drawbacks.The crossover points for each pixel are computed adaptively based on the local feature of the neighborhood of each pixel.A new fuzzy membership function is proposed of which membership function is S-shape,and can combined with the crossover points perfectly by adjusting the parameters.Road surface images with changeful grey levels can obtain satisfactory enhancement effect by the new algorithm.And the new algorithm is universal because all the parameters are computed adaptively.更多还原