Chen Guo, Li Li, Jin Weiqi, Zhu Jin, Shi Feng
Opt Express. 2019 Apr 15;27(8):10564-10579. doi: 10.1364/OE.27.010564.
Most imaging devices lose image information during the acquisition process due to their low dynamic range (LDR). Existing high dynamic range (HDR) imaging techniques have a trade-off with time or spatial resolution, resulting in potential motion blur or image misalignment. Current HDR methods are based on the fusion of multi-frame LDR images and can suffer from blurring of fine details, image aliasing, and image boundary effects. This study developed a dual-channel camera (DCC) to achieve HDR imaging, which can eliminate image motion blur and registration problems. Considering the output characteristics of the camera, we propose a weighted sparse representation multi-scale transform fusion algorithm, which fully preserves the original image information, while eliminating image aliasing and boundary problems in the fused image, resulting in high-quality HDR imaging.
大多数成像设备由于其低动态范围（LDR），在采集过程中会丢失图像信息。现有的高动态范围（HDR）成像技术在时间或空间分辨率上存在权衡，会导致潜在的运动模糊或图像配准问题。当前的HDR方法基于多帧LDR图像的融合，可能会出现精细细节模糊、图像混叠和图像边界效应。本研究开发了一种双通道相机（DCC）来实现HDR成像，它可以消除图像运动模糊和配准问题。考虑到相机的输出特性，我们提出了一种加权稀疏表示多尺度变换融合算法，该算法在充分保留原始图像信息的同时，消除了融合图像中的图像混叠和边界问题，从而实现高质量的HDR成像。
