提出了基于脊小波(ridgelet)变换域的模糊自适应图像增强算法,利用脊小波变换在表示图像线性奇异边缘时具有独特的优越性,达到突出边缘和抑制噪声的目的。利用频域内傅里叶投影变换定理,提出优化有限拉东(Radon)变换系数顺序的方法,使得拉东变换后图像的折回现象得到改善;利用广义模糊集合概念和最大模糊熵原理,提出一种自适应设置模糊增强函数方法,使得增强后的图像在抑制噪声、增强特征方面达到较好折衷。通过模拟实验显示,该算法优于传统的增强方式,在低信噪比情况(2.5～5.5 dB)下,其边缘检测概率大于二维小波增强方式约50%。应用于含有局部线形裂纹的路面病害图像的增强,可以将裂纹信号基本增强出来,且对路面上离散的油滴、石子等点噪声抑制较好。

The implement algorithm of adaptive fuzzy image enhancement is proposed in ridgelet transform domain. Making use of the unique superiority for representing the linear singular border, the ridgelet transform can reach the aim of outstanding the border and restraining the noise. Applying the Fourier projection theorem in the frequency domain, the method is proposed for optimizing the ordering of the finite Radon transform coefficients. As can be seen, the “wrap around” effect is reduced in the image disposed by the Radon transform. The algorithm of adaptive fuzzy image enhancement is put forward based on the generalized fuzzy set and the maximum fuzzy entropy. The processed image is the better compromise between enhancing the characteristics and inhibiting the noise. The experiment shows that the edge detection probability of this algorithm is greater than the traditional ones' with approximate 50% under the condition of low signal-noise ratio (2.5～5.5 dB). Applying the algorithm to enhance the linear cracks in the road surface image, we can enhance the crack signals and restrain the discrete noise, such as oil droplet , cobblestone.