摘要
图像的暗通道是由图像的分块区域中最低颜色分量值组成的图像通道。图像的暗通道在图像去雾、估算物体距离和计算图像中雾霾浓度等方面有着重要的作用。根据暗通道定义计算图像暗通道时,图像中的每一个像素点都需要被处理,算法比较耗时。针对这一缺点,进一步分析暗通道的原有计算方法,提出一种基于暗点优先膨胀的计算图像暗通道优化算法。实验结果表明,该优化算法只需要处理部分像素点就可以得到与原算法相同的结果,并在处理速度上比原算法提高了一个数量级。
Image＇ s dark channel is the image channel consisted of the lowest value of colour components in image＇ s chunking area. Dark channel of image plays important roles in application of image haze removal, object distance estimation, haze density computation and so on. When the dark channel is computed according to its definition, every pixel point in the image has to be processed and the processing course is time-consuming. To improve this shortage, the original dark channel computation method is further analysed, and an optimised algorithm of computing image＇ s dark channel based on dark point priority expansion is proposed in the article. Experimental result shows that, the optimised algorithm can achieve the same result as the origin one by processing just part of the pixel points, its processing speed raises one order of magnitude.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第7期137-140,共4页
Computer Applications and Software
基金
国家自然科学基金项目(60803160
61100133
61272110)
武汉市科技攻关计划项目(201110821236)
武汉市科技局晨光计划项目(201150431095
关键词
图像暗通道
暗点优先膨胀
暗通道优先
Dark channel of image
Dark point priority expansion
Dark channel prior
