基于子带分解多尺度Retinex的红外图像自适应细节增强

为实现高动态范围红外图像压缩和高亮区与阴影区细节增强，提出一种基于子带分解多尺度Retinex自适应细节增强方法。利用子带分解多尺度Retinex 获取三个独立光谱子带；利用引导滤波将各子带分为细节层和基础层；之后依据子带特性设计细节增强权值基函数，自适应实现红外图像细节增强；针对输出图像平滑区灰度不均匀特点，自适应求取Gamma 曲线实现灰度映射。实验结果表明：经本文算法处理后图像阴影区与高亮区细节得到明显增强，全局视觉效果良好。客观测评结果表明：本文算法有效增强图像细节信息，并且与经典基于双边滤波的细节增强算法比较，本文算法耗时没有增加。

Abstract

An adaptive detail enhancement method based on subband-decomposed multi-scale Retinex is proposed to deal with high dynamic range compression of infrared images and detail enhancement in both high light regions and dim regions. Three independent spectrum subbands using subband- decomposed multi- scale Retinex are gained. Then guided image filter is applied to get detail layer and base layer from each subband. Later the basis weight function for detail enhancement is proposed according to characteristic of separate spectrum subband. Adaptive detail enhancement is achieved with basis weight function. In order to eliminate the nonuniformity of gray intensity in the outcome image, a new adaptive way to get Gamma curve for gray value remapping is put forward. Experimental results show that the detail of the enhanced images is upgraded greatly in both high light regions and dim regions, and have a satisfied visual effect. Objective evaluation parameters illustrate that the proposed algorithm can effectively enhance detail of infrared images. In addition, the time consuming is not lengthened compared to other algorithms in the experiment.

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李毅, 张云峰, 李宁, 方艳超, 吕春雷, 于国权, 陈娟. 基于子带分解多尺度Retinex的红外图像自适应细节增强[J]. 中国激光, 2015, 42(5): 0512001. Li Yi, Zhang Yunfeng, Li Ning, Fang Yanchao, Lü Chunlei, Yu Guoquan, Chen Juan. Adaptive Detail Enhancement for Infrared Image Based on Subband-Decomposed Multi-Scale Retinex[J]. Chinese Journal of Lasers, 2015, 42(5): 0512001.

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