论文标题
增量非规范图像采样模式的设计技术
Design Techniques for Incremental Non-Regular Image Sampling Patterns
论文作者
论文摘要
即使通常在常规的二维网格上获取图像信号，但存在许多可能的采样场景。非规范采样可以消除混叠。就非规范采样模式而言，如何实际安排采样位置有很高的自由度。在文献中，与正常模式相比，随机模式显示出更高的重建质量，这是由于混叠效应降低而导致的。缺点，随机模式具有很大的空隙区域，这也是不利的。在这项工作的范围内，我们提出了两种技术来设计优化的非规范图像采样模式，以进行任意采样密度。两种技术都会创建增量采样模式，即，在每个步骤中添加一个像素位置，直到达到所需的采样密度为止。我们提出的模式在PSNR中的重建质量在较大的密度范围内将重建质量提高了+0.5 dB以上。提供了视觉比较。
Even though image signals are typically acquired on a regular two dimensional grid, there exist many scenarios where non-regular sampling is possible. Non-regular sampling can remove aliasing. In terms of the non-regular sampling patterns, there is a high degree of freedom in how to actually arrange the sampling positions. In literature, random patterns show higher reconstruction quality compared to regular patterns due to reduced aliasing effects. On the downside, random patterns feature large void areas which is also disadvantageous. In the scope of this work, we present two techniques to design optimized non-regular image sampling patterns for arbitrary sampling densities. Both techniques create incremental sampling patterns, i.e., one pixel position is added in each step until the desired sampling density is reached. Our proposed patterns increase the reconstruction quality by more than +0.5 dB in PSNR for a broad density range. Visual comparisons are provided.
