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.

翻译：针对图像在大角度仿射变换（角度超过50度）下特征提取稳定性显著下降的问题，目前仍缺乏令人满意的解决方案。即使是基于SIFT构建、通过大量仿射变换模拟图像对比的ASIFT方法，也不可避免地存在耗时较长、内存占用要求高的缺点，且在大视角仿射变换下特征提取稳定性急剧下降。为此，我们提出一种改进ASIFT的方法。在提升精度并保持仿射不变性的前提下，该方法目前是我们所知处理超仿射图像最快的特征提取方法。同时，其针对仿射变换图像的特征提取稳定性已接近理论极限——拍摄方向与被摄物体法线方向的夹角（绝对倾斜角）以及两幅图像间的拍摄变换角度（相对倾斜角）均可接近90度。该方法的核心思想在于：通过参考图像的仿射变换模拟获取最优参数集，并基于该参数集结合Lanczos插值复现模拟的仿射变换。随后将其与具有优异实时性能的ORB算法结合，实现快速定向二进制描述。此外，通过引入尺度参数模拟进一步提升了运算效率。