有损压缩的视频图像去雾算法  

Defogging Algorithm of Lossy Compression Video Image

作　　者：李龙利[1] 刘清[1] 郭建明[1] 周生辉[1] 

机构地区：[1]武汉理工大学自动化学院,武汉430070

出　　处：《模式识别与人工智能》2011年第6期833-838,共6页Pattern Recognition and Artificial Intelligence

基　　金：湖北省自然科学基金资助项目(No.2009CDB403)

摘　　要：传统的去雾算法对一般工业采集的有损压缩视频图像进行去雾,不仅不能满足实时性要求,而且会形成许多不规则区域,造成去雾后出现很多颜色不均匀的杂点区域,去雾效果不理想.文中提出利用小波变换可将图像分成高频和低频子带这一显著特点来帮助找出这些不规则区域,从而对不规则区域的透射率进行处理,再采用暗原色先验算法实现图像复原以后,消除颜色不均匀现象,最终对有损压缩图像获得理想的去雾效果.同时针对传统暗原色先验方法中的抠图算法需要耗费大量运算的问题,提出结合线性内插值平滑和阈值复原的方法代替抠图算法,有效减少存储容量,缩短计算时间,提高算法的实时性.仿真结果证明文中算法的有效性.The traditional defogging algorithm used in the conventional industrial images acquired by the lossy compression of video images can＇t meet the real time constraint. And it also will form a number of irregular regions. The irregular regions cause lots of regions of color non-uniformity after defogging and seriously affect defogging result. Wavelet transform is presented to divide image into high and low frequency sub-band to find out the irregular regions. Then the transmissions of these regions are treated. And the image is recovered by using dark channel prior. Meanwhile, aiming at the problem that much more complicated computation in the matting algorithm of traditional dark channel prior is required, the method of the combination of linear interpolation smoothing and threshold recovery is proposed to instead of the matting algorithm. Thus, storage capacity and computation complexity are reduced effectively. The proposed algorithm meets the real-time request. Simulation results show the effectiveness of the proposed algorithm.

关 键 词：有损压缩 视频图像 去雾 暗原色先验 小波变换 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]