Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a method based on Frequency-domain Information of Local Energy Response called FILER. The core of FILER is the local energy response model based on frequency-domain information, which can overcome the effect of nonlinear intensity differences. To improve the robustness to local nonlinear geometric distortions and noises, we design a new edge structure enhanced feature detector and convolutional feature weighted descriptor, respectively. In addition, FILER overcomes the sensitivity of the frequency-domain information to the rotation angle and achieves rotation invariance. Extensive experiments multimodal image pairs show that FILER outperforms other state-of-the-art algorithms and has good robustness and universality.
View on arXiv@article{yang2025_2503.20827,
title={ Multimodal Image Matching based on Frequency-domain Information of Local Energy Response },
author={ Meng Yang and Jun Chen and Wenping Gong and Longsheng Wei and Xin Tian },
journal={arXiv preprint arXiv:2503.20827},
year={ 2025 }
}