Abstract: A novel low contrast image enhancement approach based on the second generation curvelet is proposed.It overcomes the shortcomings of conventional methods，such as sensitively to noise and local over-enhancement.Firstly，the source image is decomposed by Curvelet transform.Then a kind of nonlinear enhancing function is applied to enhance the image’s global contrast in the low frequency subbands，and combining threshold denoising method with non-linear gain method to reduce the noise and enhance the details of image at each scale in the high frequency subbands.Finally，the enhanced coefficients are reconstructed to obtain enhanced image.Experimental results show that the proposed approach is superior to both histogram equalization and wavelet based contrast enhancement，it can preserve image edges and reduce the noise while enhancing contrast of the image，and also has good visual effect.

摘要： 针对传统图像增强方法用于低对比度图像时，存在对噪声敏感、局部过增强等问题，提出了一种基于第二代 Curvelet 变换的增强方法。将图像进行多尺度多方向的 Curvelet 变换；引入分段非线性函数的思想，调整低频子带系数，提高图像整体的对比度；对各尺度的高频子带系数进行非线性加权，增强图像细节，并进行阈值降噪。实验表明，该方法优于常用的空间域直方图均衡化和小波域图像增强法，能有效地提高图像的对比度、降低噪声，并且较好地保留边缘信息，具有良好的视觉效果。