基于视觉特性的非线性多尺度彩色图像增强

Non-linear multi-scale color image enhancement based on human visual system

[目的]针对图像在低光照下的亮度和对比度偏低的问题,提出一种基于视觉特性的非线性多尺度彩色图像增强算法。[方法]该算法将彩色图像从RGB色彩空间转化到HSI色彩空间,保持H分量不变,对S分量进行指数拉伸,对I分量利用视觉系统模型和非线性映射方法实现图像对比度增强,再通过自适应的亮度调整增加图像的全局亮度。最后将HSI色彩空间转化到RGB色彩空间,从而实现对彩色图像自适应增强。[结果]通过对低光照彩色图像进行增强测试,其测试结果表明,[结论]该算法能够自适应地调整图像的全局亮度,增加图像的局部细节对比度,并保持其原色彩,提升彩色图像在低光照下的视见度。

Concerning that the darkness and low contrast of low illumination image, a non-linear multi-scale color image enhancement algorithm based on visual characteristics is proposed. Firstly, color image is transformed from the RGB to HSI color space and keep the component H unchanged. Secondly, the component S is processed with exponential method. Thirdly, the component I is processed by visual system model and non-linear mapping to achieve contrast enhancement. Meanwhile, images＇ global luminance is adjusted with self-adapting method. In the end, the image is transformed back to RGB color space to achieve a color image a- daptive enhancement. According to testing many color images with low luminance, the results shows that the algorithm can adjust image global brightness adaptively, increase local contrast in details, maintain its original color and improve the visibility of the light images.