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POCS Super-Resolution Sequence Image Reconstruction Based on Improvement Approach of Keren Registration Method

机译:基于Keren注册方法改进方法的POCS超分辨率序列图像重建

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This paper introduces the keren sub-pixel registration method and point out its disadvantage. Moreover, this paper put forward a new improvement approach about keren method and its iterative method. The improvement approach takes the four parameters affine transformation model instead of the rigid body transformation model. This change avoids the error that is brought on by the tailor series expansion of angle and improves the precise of image registration greatly. The experiment shows that the improvement approach makes less absolute error of angle than keren method and its iterative algorithm. The improvement approach makes the absolute error of translation parameters under 0.1 pixels in the case of the rotation angel of 15 degree and under 0.01 pixels in the case of the small rotation angle using our pictures. At last, the Projection Onto Convex Set (POCS) method is used to reconstruct high-resolution image from several low-resolution image sequences. As a result, we find that the reconstruction algorithm based on our improvement registration approach has better effect than the reconstruction algorithm based on keren iterative registration method.
机译:本文介绍了Keren子像素注册方法并指出其缺点。此外,本文提出了一种关于Keren方法的新改进方法及其迭代方法。改进方法采用四个参数仿射变换模型而不是刚体变换模型。这一变化避免了由角度裁缝串联扩展所带来的错误,并大大提高了图像注册的精确性。实验表明,改善方法比Keren方法和迭代算法较少的角度误差。改进方法在旋转天使的情况下为0.1像素下的翻译参数的绝对误差在使用我们的照片的小旋转角度的情况下为15度和0.01像素。最后,将投影到凸起集(POCS)方法用于重建来自几个低分辨率图像序列的高分辨率图像。结果,我们发现基于我们的改进登记方法的重建算法比基于Keren迭代登记方法的重建算法更好。

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