The fusion of images from dual camera systems featuring a wide-angle and a telephoto camera has become a hotspot problem recently. By integrating simultaneously captured wide-angle and telephoto images from these systems, the resulting fused image achieves a wide field of view (FOV) coupled with high-definition quality. Existing approaches are mostly deep learning methods, and predominantly rely on supervised learning, where the training dataset plays a pivotal role. However, current datasets typically adopt a data synthesis approach generate input pairs of wide-angle and telephoto images alongside ground-truth images. Notably, the wide-angle inputs are synthesized rather than captured using real wide-angle cameras, and the ground-truth image is captured by wide-angle camera whose quality is substantially lower than that of input telephoto images captured by telephoto cameras. To address these limitations, we introduce a novel hardware setup utilizing a beam splitter to simultaneously capture three images, i.e. input pairs and ground-truth images, from two authentic cellphones equipped with wide-angle and telephoto dual cameras. Specifically, the wide-angle and telephoto images captured by cellphone 2 serve as the input pair, while the telephoto image captured by cellphone 1, which is calibrated to match the optical path of the wide-angle image from cellphone 2, serves as the ground-truth image, maintaining quality on par with the input telephoto image. Experiments validate the efficacy of our newly introduced dataset, named ReWiTe, significantly enhances the performance of various existing methods for real-world wide-angle and telephoto dual image fusion tasks.

翻译：广角与长焦双相机系统的图像融合近年来成为热点问题。通过整合系统同步捕获的广角和长焦图像，融合图像可同时实现宽视场（FOV）与高清画质。现有方法多为深度学习方法，其中监督学习占据主导地位，训练数据集起着关键作用。然而，当前数据集通常采用数据合成方法生成广角-长焦输入对及真值图像。值得注意的是，广角输入由合成数据而非真实广角相机捕获，且真值图像由广角相机拍摄，其质量显著低于长焦相机捕获的输入图像。为解决上述局限，我们提出一种基于分束器的新型硬件装置，可从两台配备广角-长焦双摄像头的真实手机同步捕获三幅图像，即输入对与真值图像。具体而言，手机2捕获的广角与长焦图像作为输入对，手机1捕获的长焦图像（通过标定使其光路与手机2的广角图像一致）作为真值图像，其质量与输入长焦图像保持同等水平。实验验证了我们新提出的ReWiTe数据集的有效性，该数据集可显著提升现有方法在真实场景广角与长焦双图像融合任务中的性能。