摘要
本文提出一种新颖的基于运动目标的De-interlace算法.该算法以实际的运动目标作为操作对象,引入一种较精确的运动目标提取方法,并采用免疫克隆选择算法加速匹配目标的搜索过程.新算法融合了运动补偿、中值滤波、Weave、Bob等De-interlace方法.与流行的基于运动块补偿的De-interlace算法相比,新算法更适应复杂的视频序列,不仅可以处理平移运动,还适用于旋转、尺度变换等复杂运动情况.
A novel de-interlacing algorithm based on moving objects is presented. In this algorithm, natural moving objects, not contrived blocks, are considered as the processing basic cells. And an accurate method is introduced to detect the moving objects with the immune clonal selection algorithm accelerating the search process for matching objects. This algorithm integrates many other de-interlacing methods such as motion compensation, median filtering, Weave and Bob, so it is more adaptive to various complex video sequences. Moreover, it can perform the motion compensation for the objects with not only the translation, but also the rotation and scaling transform. The experimental results illustrate that compared with the block matching method with full search, the new de-interlacing algorithm greatly improve the efficiency and performance.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2005年第6期1066-1069,共4页
Acta Electronica Sinica
基金
国家自然科学基金(No.60202004)
教育部重点项目(No.104173)
