基于HSI色彩空间的微光图像增强算法

Fan Wu, U. KinTak
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引用次数: 11

摘要

为了提高弱光图像的质量,提出了一种新的基于HSI的增强算法。该算法在保持图像对比度和细节的同时,增强了微光图像的亮度。首先将原始RGB图像转换为HSI色彩空间,然后对强度和饱和度分量进行不同的增强方法处理,但色相分量不变,对饱和度分量S应用分割指数增强算法,然后对强度分量I应用直方图均衡化,然后用小波变换将强度分量I划分为高低频子带;将Retinex算法应用于低频子带调整图像亮度,将改进的模糊增强应用于高频子带增强图像细节。最后对分量I进行小波逆变换重构,将重构后的分量I与H和增强后的S分量合成,得到清晰的RGB图像。利用HSI色彩空间和改进的增强算法,实现了对低照度彩色图像的增强。实验结果表明,该算法能明显改善弱光彩色图像的视觉效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low-Light image enhancement algorithm based on HSI color space
To improve the quality of low-light image, we proposed a new HSI based enhancement algorithm. This new algorithm enhances the luminance of low-light level images while preserving image contrast and details. First, the original RGB image is converted into HSI color space, then the intensity and saturation components are processed with different enhancement methods, but the hue component remains unchanged, the segmentation exponential enhancement algorithm is applied to saturation component S, then apply the histogram equalization to intensity component I and then the intensity component I is divided into high and low frequency sub-bands with wavelet transform, the Retinex algorithm is applied to the low frequency sub-band to adjust image luminance while the improved fuzzy enhancement is applied to the high frequency sub-band to enhance image details. Finally, reconstruct the component I with inverse wavelet transform, and the reconstructed component I will be synthesized with H and the enhanced S components to get a clear RGB image. By taking advantage of HSI color space and the improved enhancement algorithm, the enhancement of low illumination color image has been achieved. According to the experiment results, this algorithm can obviously improve the visual effect of low light color image.
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