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A superresolution imaging method based on dense subpixel-accurate motion fields

机译:基于密集亚像素精度运动场的超分辨率成像方法

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A superresolution imaging method suitable for imaging objects moving in a dynamic scene is described. The main operations are performed over three threads: the computation of a dense interframe 2D motion-field induced by the moving objects at subpixel resolution in the first thread. Concurrently, each video image frame is enlarged by cascade of an ideal low-pass filter and a higher rate sampler, essentially stretching each image onto a larger grid. Then, the main task is to synthesize a higher resolution image, from the stretched image of the first frame, and that of the subsequent frames subjected to suitable motion compensation. A simple averaging process and/or a simplified Kalman filter may be used to minimize the spatio-temporal noise, in the aggregation process. The method takes advantage of widely used MPEG-4 encoding hardware/software tools. A few experimental cases are presented with a basic description of the key operations performed in the overall process.
机译:描述了一种适合于对在动态场景中移动的物体进行成像的超分辨率成像方法。主要操作在三个线程上执行:在第一个线程中以子像素分辨率计算运动对象引起的密集帧间2D运动场。同时,通过级联理想的低通滤波器和更高速率的采样器来放大每个视频图像帧,从本质上将每个图像拉伸到更大的网格上。然后,主要任务是从第一帧的拉伸图像以及经过适当运动补偿的后续帧的拉伸图像合成更高分辨率的图像。在聚合过程中,可以使用简单的平均过程和/或简化的卡尔曼滤波器来最小化时空噪声。该方法利用了广泛使用的MPEG-4编码硬件/软件工具。给出了一些实验案例,并对整个过程中执行的关键操作进行了基本描述。

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