Infrared Video Dynamic Range Compression Based on Global and Local Temporal Coherence

Dynamic range compression (DRC) for infrared (IR) video aims to compress high dynamic range (HDR) IR video into low dynamic range (LDR) IR video, facilitating display on common devices and enhancing visual perception. This research requires balancing the preservation of spatial and temporal information, particularly detail preservation and temporal brightness coherence. However, existing methods fail to simultaneously maintain both global and local temporal coherence due to the lack of distinction between global and local motion, which inevitably introduces flickering and reduces the visual experience. To address this issue, this article proposes an IR video DRC (vDRC) method based on lobal and local temporal coherence. Specifically, a motion mask strategy based on structural similarity is introduced to differentiate between global motion regions, local motion regions, and static regions. A motion estimation strategy using different block-matching scales is then applied to estimate HDR motion information between consecutive frames, which is used to constrain the LDR of the previous frame and construct a temporal constraint term to preserve both lobal and local temporal coherence. Extensive experiments conducted on two public IR video datasets demonstrate that the proposed method outperforms state-of-the-art methods both quantitatively and qualitatively, offering a more effective solution for IR vDRC and enhancing visualization.