红外技术, 2017, 39 (5): 421, 网络出版: 2017-06-06
基于视觉显著性与对比度增强的红外图像融合
Infrared Image Fusion Based on Visual Saliency and Contrast Enhancement
图像增强 图像融合 视觉显著性 自适应引导滤波 多尺度 Retinex image enhancement image fusion visual saliency adaptive guided filter NSCT NSCT multi-scale Retinex
摘要
目前传统多尺度分析红外图像融合算法存在以下不足: 融合图像的对比度改善效果有限, 无法获取图像的某些细节信息; 融合规则仅考虑单一特征, 故未能突出目标特征。针对以上问题, 本文提出一种基于视觉显著性与对比度增强的红外图像融合算法。首先对待融合的图像进行基于自适应引导滤波的多尺度 Retinex图像增强, 然后利用 NSCT对图像进行多尺度分解, 最后利用图像视觉显著性融合低频系数, 采用基于窗口的系数融合带通系数。实验证明, 该算法获得的红外融合图像效果明显优于传统方法。
Abstract
Traditional infrared image fusion by multi-scale analysis has some disadvantage: the fused image cannot improve contrast, some details of the image cannot be caught; Fusion rules only depend on single feature, causing that the key target features in the scene of the fused image cannot be highlighted. To solve the above problems, in this paper, an infrared image fusion algorithm based on visual saliency and contrast enhancement is proposed. Firstly, the image is enhanced by using the algorithm of multi-scale Retinex based on adaptive guided filter; then, the image is decomposed by NSCT; finally, we use visual saliency to guide fusing the low frequency coefficient, using coefficient based on window to fuse band pass coefficient. The experimental results show that the fusion effect is superior to the traditional method.
张承泓, 李范鸣, 吴滢跃. 基于视觉显著性与对比度增强的红外图像融合[J]. 红外技术, 2017, 39(5): 421. ZHANG Chenghong, LI Fanming, WU Yingyue. Infrared Image Fusion Based on Visual Saliency and Contrast Enhancement[J]. Infrared Technology, 2017, 39(5): 421.