Low illumination color image enhancement based on improved Retinex

摘要

Low illumination color image usually has the characteristics of low brightness, low contrast, detail blur and high salt and pepper noise, which greatly affected the later image recognition and information extraction. Therefore, in view of the degradation of night images, the improved algorithm of traditional Retinex. The specific approach is: First, the original RGB low illumination map is converted to the YUV color space (Y represents brightness, UV represents color), and the Y component is estimated by using the sampling acceleration guidance filter to estimate the background light; Then, the reflection component is calculated by the classical Retinex formula and the brightness enhancement ratio between original and enhanced is calculated. Finally, the color space conversion from YUV to RGB and the feedback enhancement of the UV color component are carried out.