图像传感器在光照不足的环境下成像，会造成视频图像噪声大、对比度低、大量细节信息无法表现等问题，这些不足严重影响人们对视频图像内容的判读和理解。分析了低照度视频图像的不足，总结了近年来针对这些不足提出的有代表性的一些低照度视频图像增强策略及它们的衍生算法。根据这些算法的亮度增强原理将它们分为基于色调映射、背景融合、模型、直方图等几大类，并对比分析了它们各自的适用场合、算法优势、局限性等。%Imaging under the condition of insufficient illumination with the image sensor will cause the video image noise, low contrast and a lot of details cannot be expressed etc., these problems seriously affect people to understand and interpret the content of the video image. This paper analyzes the characteristics of low-light video images, and summarizing representative of some of the low-light image enhancement algorithm strategies and their derivatives based on the characteristics in recent years. The algorithms are divided into Tone Mapping,background fusion,model,map-ping function according to the principal of light enhancement,and their respective applications,algorithm advantages and limitations are also analyzed by comparing them.
展开▼
