中文摘要：

实时、鲁棒的图像配准是航拍视频电子稳像、全景图拼接和地面运动目标自动检测与跟踪的前提和关键技术．本文以航拍视频序列为处理对象，提出了一种新的基于场景复杂度与不变特征的实时配准算法，其主要特点包括：（1）在对航拍视频配准难点进行详细分析的基础上，有针对性的提出基于积分图的快速图像尺度空间构建、依据场景复杂度的检测特征点数量在线精确控制、基于描述子误差分布统计特性级的联分类器构造等新方法，使得算法配准性能不随场景的复杂度发生改变，能够在各种地貌条件下实时、稳定的进行图像配准；（2）将多尺度Harris角点和SIFT描述子相结合，并通过对帧间变换模型参数进行鲁棒估计，保证了算法具有良好的旋转、尺度、亮度不变性和配准精度．实验结果表明，算法可在场景变化、图像大幅度平移、尺度缩放和任意角度旋转等复杂条件下实时、精确的进行图像配准，对分辨率为320×240的航拍序列的平均处理速度达到20．7帧／秒．

英文摘要：

Real-time and robust image registration is the premise and key technology of aerial video stabilization,panorama stitching and ground moving target detection and tracking. This paper presents a novel scene complexity and invariant feature based aerial video registration algorithm. The main characteristics of the proposed method include： （ 1 ） Based on analyzing the key difficulties and challenges of aerial video registration,several new methods are presented to reafize fast and effective video registration under various real scenes, include integral image based fast image scale space generation, scene complexity based feature number controlling, and statistical error distribution of correspond features based cascade filtering. （2） Through combining the multi-scale Harris comer detection, SIFT （Scale Invarianu Feature Transform） feature description, and the RANSAC （Random Sample Consensus） based frame geometry transfomation parameters estimation, the proposed algorithm achieves satisfied rotation, scaling, brightness invariance and accuracy of registration. Experiment results show that the proposed algorithm carries out real-time and precise image registration under complex conditions with change of scene, large image translation, scaling and arbitrary rotation, and the average processing speed for a resolution of 320×240 unmanned aerial video sequences achieves 20.7fps.