Abstract
Infrared image super-resolution (IISR) under real-world conditions is a practically significant yet rarely addressed task. Pioneering works are often trained and evaluated on simulated datasets or neglect the intrinsic differences between infrared and visible imaging. In practice, however, real infrared images are affected by coupled optical and sensing degradations that jointly deteriorate both structural sharpness and thermal fidelity. To address these challenges, we propose Real-IISR, a unified autoregressive framework for real-world IISR that progressively reconstructs fine-grained thermal structures and clear backgrounds in a scale-by-scale manner via thermal-structural guided visual autoregression. Specifically, a Thermal-Structural Guidance module encodes thermal priors to mitigate the mismatch between thermal radiation and structural edges. Since non-uniform degradations typically induce quantization bias, Real-IISR adopts a Condition-Adaptive Codebook that dynamically modulates discrete representations based on degradation-aware thermal priors. Also, a Thermal Order Consistency Loss enforces a monotonic relation between temperature and pixel intensity, ensuring relative brightness order rather than absolute values to maintain physical consistency under spatial misalignment and thermal drift. We build FLIR-IISR, a real-world IISR dataset with paired LR-HR infrared images acquired via automated focus variation and motion-induced blur. Extensive experiments demonstrate the promising performance of Real-IISR, providing a unified foundation for real-world IISR and benchmarking. The dataset and code are available at: this https URL.
Abstract (translated)
在现实条件下进行红外图像超分辨率（IISR）是一项具有实际意义但较少被关注的任务。早期的工作通常是在模拟数据集上训练和评估，或者忽视了红外成像与可见光成像之间的内在差异。然而，在实践中，真实的红外图像受到光学和感测退化的共同影响，这些退化同时降低了结构清晰度和热辐射的准确性。为了应对这一挑战，我们提出了Real-IISR，这是一个统一的自回归框架，用于现实世界的IISR任务。该框架通过基于热-结构引导的视觉自回归逐步以逐级的方式重建精细的热结构和清晰的背景。 具体而言，一个热-结构引导模块编码了热先验信息来缓解热辐射与结构边缘之间的不匹配问题。由于非均匀退化通常会引起量化偏置，Real-IISR采用了一个条件自适应码本，该码本根据对退化的感知性热先验动态地调节离散表示。此外，一种温度顺序一致性损失被提出以强制执行温度和像素强度之间单调关系，确保相对亮度排序而不是绝对值，在空间错位和热漂移的情况下保持物理一致性。 我们构建了FLIR-IISR数据集，这是一个包含配对的低分辨率-高分辨率红外图像的真实世界IISR数据集。这些图像通过自动化焦距变化和运动引起的模糊获得。广泛的实验展示了Real-IISR的出色性能，为真实世界的IISR提供了统一的基础并设立了基准。该数据集和代码可在以下网址获取：此 https URL 链接。
URL
https://arxiv.org/abs/2603.04745
