提出一种快速精准的超仿射图像特征点提取方法,显著提升大角度变换下的稳定性。
Feature Point Extraction for Extra-Affine Image
- 通过优化参数模拟仿射变换并结合Lanczos插值,提升特征提取精度。
- 在接近90度的视角变换下,特征稳定性逼近理论极限,速度优于ASIFT。
- 适合需要实时处理大角度图像变换的场景,如无人机影像分析。
针对大角度仿射变换(超过50度)下特征提取稳定性严重下降的问题,现有方法如ASIFT虽基于SIFT且具备仿射不变性,但仍存在计算耗时、内存占用高、大视角下性能骤降等缺陷。为此,本文提出一种改进方法:在保持仿射不变性的前提下,通过参考图像模拟最优仿射变换参数,并基于该参数集结合Lanczos插值重建变换图像;随后与ORB结合,实现快速二值化描述子生成;同时引入尺度参数模拟进一步提升效率。实验表明,在拍摄方向与物体法线夹角(绝对倾角)及两图间转换倾角均接近90度的极端条件下,特征提取稳定性已逼近理论上限,当前为已知最快的超仿射图像特征提取方法。
原文摘要 · Abstract (English)
The issue concerning the significant decline in the stability of feature extraction for images subjected to large-angle affine transformations, where the angle exceeds 50 degrees, still awaits a satisfactory solution. Even ASIFT, which is built upon SIFT and entails a considerable number of image comparisons simulated by affine transformations, inevitably exhibits the drawbacks of being time-consuming and imposing high demands on memory usage. And the stability of feature extraction drops rapidly under large-view affine transformations. Consequently, we propose a method that represents an improvement over ASIFT. On the premise of improving the precision and maintaining the affine invariance, it currently ranks as the fastest feature extraction method for extra-affine images that we know of at present. Simultaneously, the stability of feature extraction regarding affine transformation images has been approximated to the maximum limits. Both the angle between the shooting direction and the normal direction of the photographed object (absolute tilt angle), and the shooting transformation angle between two images (transition tilt angle) are close to 90 degrees. The central idea of the method lies in obtaining the optimal parameter set by simulating affine transformation with the reference image. And the simulated affine transformation is reproduced by combining it with the Lanczos interpolation based on the optimal parameter set. Subsequently, it is combined with ORB, which exhibits excellent real-time performance for rapid orientation binary description. Moreover, a scale parameter simulation is introduced to further augment the operational efficiency.
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