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摘要: 超分辨率图像重建技术指通过融合多幅变形、模糊、有噪、频谱混叠的低分辨率降质图像来重建一幅高质量高分辨率图像. 凸集投影 (POCS) 算法是一种广泛使用的超分辨率图像重建方法. 本文提出了一种适用于 POCS 算法的改善高分辨率重建图像边缘质量的方法. 该方法将中心在边缘像素的点扩散函数 (PSF) 与一个指数型权值函数相乘, 使得修改的 PSF 系数沿着边缘正交的方向减小. 实验结果表明, 这样的修改有效地保持了边缘的特性, 明显地提高了重建图像的质量
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关键词:
- 分辨率图像重建 /
- 凸集投影(POCS) /
- 边缘检测 /
- 点扩散函数(PSF)
Abstract: Super-resolution image reconstruction refers to as restoring a high-resolution and high-quality image from multiple low-resolution observations degraded by warping, blurring, noise and aliasing. The projections onto convex sets (POCS) algorithm is widely used for super-resolution image reconstruction. In this paper, we propose an improved POCS algorithm that reduces the amount of edge artifacts present in the high-resolution reconstructed image. The blur point spread function (PSF) centered at an edge pixel is weighted by an exponential function, so that the coefficients of the modified PSF could decrease in the direction orthogonal to the edge. Experimental results show that the modification effectively reduces the visibility of the artifacts on the edges and obviously improves the quality of the reconstructed image.
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