IEEE Trans Image Process. 2016 Mar;25(3):1017-32. doi: 10.1109/TIP.2015.2512381.
Subpixel-based image scaling can improve the apparent resolution of displayed images by controlling individual subpixels rather than whole pixels. However, improved luminance resolution brings chrominance distortion, making it crucial to suppress color error while maintaining sharpness. Moreover, it is challenging to develop a scheme that is applicable for various subpixel arrangements and for arbitrary scaling factors. In this paper, we address the aforementioned issues by proposing a generalized continuous-domain analysis model, which considers the low-pass nature of the human visual system (HVS). Specifically, given a discrete image and a grid-like subpixel arrangement, the signal perceived by the HVS is modeled as a 2D continuous image. Minimizing the difference between the perceived image and the continuous target image leads to the proposed scheme, which we call continuous-domain analysis for subpixel-based scaling (CASS). To eliminate the ringing artifacts caused by the ideal low-pass filtering in CASS, we propose an improved scheme, which we call CASS with Laplacian-of-Gaussian filtering. Experiments show that the proposed methods provide sharp images with negligible color fringing artifacts. Our methods are comparable with the state-of-the-art methods when applied on the RGB stripe arrangement, and outperform existing methods when applied on other subpixel arrangements.
基于子像素的图像缩放可以通过控制单个子像素而不是整个像素来提高显示图像的表观分辨率。然而，提高亮度分辨率会带来色度失真，因此在保持锐度的同时抑制颜色误差至关重要。此外，开发一种适用于各种子像素排列和任意缩放因子的方案具有挑战性。在本文中，我们通过提出一种考虑到人眼视觉系统 (HVS) 低通特性的广义连续域分析模型来解决上述问题。具体来说，给定一幅离散图像和一种网格状的子像素排列，HVS 感知的信号被建模为一幅 2D 连续图像。最小化感知图像和连续目标图像之间的差异会导致提出的方案，我们称之为基于子像素缩放的连续域分析 (CASS)。为了消除 CASS 中理想低通滤波引起的振铃伪像，我们提出了一种改进的方案，我们称之为带有拉普拉斯高斯滤波的 CASS。实验表明，所提出的方法提供了具有可忽略颜色边缘伪像的清晰图像。当应用于 RGB 条纹排列时，我们的方法与最先进的方法相当，而当应用于其他子像素排列时，我们的方法优于现有方法。
