一种基于参数自适应引导滤波的红外图像细节增强算法

An Infrared Image Detail Enhancement Algorithm Based on Parameter Adaptive Guided Filtering

摘要: 图像分层滤波器中引导滤波器因其滤波保边效果好和计算复杂度低，在红外图像细节增强领域得到了广泛的研究与应用。但传统的引导滤波器固定的正则化参数ε不能在所有场景下都取得较好的滤波分层效果，所以本文提出基于局部方差的参数ε自适应算法，以提高引导滤波器场景适应性。此外本文进一步通过自适应参数ε值，提出了改进的基于噪声掩膜函数的细节层自适应增强算法，从而在有效抑制了图像噪声水平同时提高了算法在不同场景下的细节增强能力。

Abstract: Of all the image layered filters, guided filter has been widely studied and applied in the field of infrared image detail enhancement because of its good edge preserving effect and low computational complexity. However, traditional fixed regularization parameter ε of the guide filter cannot achieve good filtering layering effect in all scenarios. Therefore, an adaptive algorithm of parameter ε based on local variance is proposed in this paper to improve the adaptability of the guide filter in all scenarios. In addition, an improved detail layer adaptive enhancement algorithm based on noise mask function is proposed by using the adaptive parameter ε value, which can effectively suppress the noise level and improve the detail enhancement ability of the algorithm in different scenes.