基于灰度级映射函数建模的多曝光高动态图像重建

Multi?exposure HDR Image Reconstruction Based on Gray Scale Mapping Function Modeling

为解决传统多曝光图像融合的实时性和动态场景鬼影消除问题,提出了基于灰度级映射函数建模的多曝光高动态图像重建算法。对任意大小的低动态范围(Low dynamic range,LDR)图像序列,仅需拟合与灰阶数目相同个数而不是与相机分辨率个数相同的视觉适应的S形曲线,利用最佳成像值判别方法直接融合,提高了算法的融合效率,能够达到实时性图像融合要求。对动态场景的融合,设计灰度级映射关系恢复理想状态的多曝光图像,利用差分法检测运动目标区域,作鬼影消除处理,融合得到一幅能够反映真实场景信息且不受鬼影影响的高动态范围图像。

To solve the real-time problem of traditional multi-exposure image fusion and ghost elimination in dynamic scenes,a multi-exposure high dynamic range(HDR)image reconstruction algorithm based on gray scale mapping function modeling is proposed.For low dynamic range(LDR)image sequence of arbitrary size,only visual adaptation S-shaped curves with the same the number of gray-scale need to be fitted,rather than the camera resolution pixels.The HDR can be achieved by fusing the best imaging values directly,which can greatly improve the efficiency of the algorithm fusion and achieve real-time requirements for dynamic scene.The ideal state of multi-exposure image can be achieved by the design of the gray level mapping function.The ghost can be eliminated through moving target detection with difference method.Finally a HDR image reflecting the real scene information and unaffected by ghosts can be achieved.