自适应双边滤波与方向梯度的红外图像增强

为克服现有的红外图像增强方法存在欠增强、过增强以及对比度不高等缺陷，提出了自适应双边滤波与方向梯度的红外图像增强方法。对双边滤波进行改进，加权系数自适应于平滑区域和细节区域，以作为Retinex的中心环绕函数，将红外图像分解为基础层和细节层；用改进的平台直方图均衡化对基础层图像进行增强；提出一种方向梯度算子，用其提取细节层图像的梯度图，进而对细节层图像进行非线性的自适应边缘增强。实验结果表明，相对于部分现有的方法，本文方法能更有效地提升红外图像的亮度和对比度，增强图像的视觉效果更佳。

Infrared Image Enhancement Based on Adaptive Bilateral Filtering and Directional Gradient

To overcome the defects of existing infrared image enhancement methods, such as under-enhancement, over-enhancement, and low contrast, an infrared image enhancement method based on adaptive bilateral filtering and directional gradient is proposed. The bilateral filter was improved, and its weighting coefficient is now adaptive to smooth and detailed regions. The improved bilateral filter is used as the central surround function of Retinex to decompose the infrared image into a base layer and a detail layer. Using improved platform histogram equalization, the base layer image is enhanced, and a directional gradient operator is proposed to extract the gradient image of the detail layer image to perform nonlinear adaptive edge enhancement on the detail-layer image. Experimental results show that, compared with existing methods, the proposed method can improve the brightness and contrast of infrared images more effectively. In addition, the visual effect of enhanced images using this method is better.