低照度图像增强算法

针对多尺度Retinex算法(MSR)以及其它图像增强算法处理后的图像峰值信噪比较低的缺陷,本文提出结合Retinex理论,根据照射分量和反射分量的特性,对二者分别采用不同的非线性函数进行调整来提高图像的对比度和增强图像细节,并在低亮度区域进行噪声抑制的方法。实验结果表明,在HSV和RGB彩色空间,运用本算法处理在低照度情况下的图像,处理后图像的峰值性噪比以及对比度高于其他算法,并且处理速度也快于MSR算法。

Algorithm of Low Illumination Image Enhancement

According to the multi-scale Retinex algorithm （MSR） defect images peak at low SNR, this paper puts forward a method of noise suppression in low luminance region according to the theory of Retinex, the characteristics of illumination and re- flection components, the two respectively by different nonlinear functions to adjust, to enhance the image contrast and enhance image detail. The experimental results show that, in HSV and RGB color space, after using this algorithm in low light, uneven il- lumination image case, the peak signal to noise ratio and the image contrast are higher than that of MSR algorithm, and the pro- cessing speed is faster than MSR algorithm.