改进多尺度Retinex理论的低照度遥感影像增强方法

由于天气和光照等外邵因素的影响，常常会出现亮度和对比度低的影像本文将基于Rctincx理论的算法和经颜色空间变换后对亮度和饱和度分量进行增强的算法进行结合，提出了一种基于多尺度Rctincx理论的改进算法，在保证色调基本不变的情况下，对亮度和饱和度进行调整，同时加入影像边缘细节特征，使增强后的影像更加符合人眼视觉特性，亮度和对比度大幅提高，影像细节更丰富，并避免了颜色失真以低照度遥感影像作为数据源，并采用清晰度、色调偏差指数和墒等影像质量评价指标验证了本文算法的有效性.

Improved Multi-scale Retinex Image Enhancement of UnderPoor Illumination

Severe atmosphere，optic，and other negative effects will result in low brightness and contract problem and there makes remote sensing image into low quality. In this paper，two kinds of algorithms based on human eye feature are analyzed with their advantages and limits.A novel optimized Retinex approach is proposed. It fuses Retinex theory and image enhancement algorithm that strengthens brightness and contrast via a color space transform. Brightness and contrast are shifted with additional image edge features while holding image hue being constant. The results from image enhancement can be more comfortable for human eye features，provide significant improvement in brightness and contrast，delivers richer image information，and avoids cross color phenomenon. The experimental data resource was a low-light-level image processed to illustrate the efficiency of our method via fineness，the hue bias exponent，entropy，and several other indexes.