结合人眼视觉特性和模糊集理论的彩色图像增强

针对不均匀光照或低照度的彩色图像对比度低的问题,提出一种结合人眼视觉特性的全局亮度调节和局部对比度增强的方法. 首先,将已有的RGB图像转换到HSV彩色空间,根据人眼视觉特性,自适应生成算法参数,非线性调节图像全局亮度和动态范围,提高图像亮度的整体水平; 然后,结合模糊集理论增强算法特性,建立局部对比度隶属度函数,非线性调整图像的局部对比度细节信息; 最后,将增强后的图像由HSV空间转换回RGB空间,完成彩色空间恢复. 实验表明,该方法能够有效地增强低照度图像的全局亮度和局部对比度,提升低照度图像的视见度.

Color Image Enhancement Combining Human VisualCharacteristics with Fuzzy Set Theory

Aiming at low illumination and contrast of color images,we propsose a novel global brightness modulation and local contrast adaptive enhancement method combined with human visual characteristics and fuzzy set theory. Firstly,through nonlinear global brightness mapping model to adjust the dynamic range of the images,the color images transform from RGB color space into HSV color space,which improves the overall level of image brightness. Next,according to fuzzy set theory,it establishes membership function to adjust the local contrast of image details nonlinearly. Finally,the enhanced images are transformed from HSV color space into RGB color space,restoring color space. Experimental results show that this algorithm has an excellent enhancement effect,which can enhance the global brightness and local contrast,and improve visibility of low illumination image.