Digital imagery and video can have content at higher resolutions than can be projected by most data projectors, which has led to a variety of techniques to improve the high-resolution perception from lower-resolution displays. However, the downsampling procedures frequently used to fit an original image or video of high-resolution into a lower-resolution projector cause a frustrating loss of fine structures in the projected imagery. Since the human visual system is more sensitive to certain image phenomena, such as text and edges, an optimal approach to preserving fine structures should further sharpen such displayed content. On the other hand, the human visual system is also very sensitive to aliasing effects in motion, such that over-sharpening can lead to significant motion artifacts.

In this paper, a new non-stationary content-adaptive resolution enhancement scheme is proposed. Our main objective in this study is to reduce the severity of artifacts due to the image enhancement processes. To achieve this goal, distribution-based text detection and hypothesis-testing-based motion detection methods are developed. Three spatial kernels, each constructed using a new band-limited Wiener deconvolution filter, are used to enhance a given image with different sharpening strengths, where the differently enhanced images are combined using a weighted non-stationary filter. For evaluation, a new visual projection assessment (VPA) dataset along with new metrics for quantifying motion artifacts are introduced. Experimental results show that the proposed non-stationary content-adaptive resolution enhancement scheme offers improved visual quality over the state-of-the-art while offering a reasonable balance between high text sharpness and reduced motion artifacts.

数字图像和视频的内容分辨率可能高于大多数数据投影仪的投影分辨率，这导致了各种技术来改善低分辨率显示器的高分辨率感知。然而，经常用于将高分辨率的原始图像或视频拟合到较低分辨率的投影仪中的下采样程序会导致投影图像中精细结构的令人沮丧的损失。由于人类视觉系统对某些图像现象（例如文本和边缘）更敏感，因此保留精细结构的最佳方法应进一步锐化此类显示内容。另一方面，人类视觉系统对运动中的混叠效应也非常敏感，因此过度锐化会导致明显的运动伪影。

在本文中，提出了一种新的非平稳内容自适应分辨率增强方案。我们在这项研究中的主要目标是减少由于图像增强过程造成的伪影的严重程度。为了实现这一目标，开发了基于分布的文本检测和基于假设检验的运动检测方法。三个空间内核，每个内核都使用新的带限维纳反卷积滤波器构建，用于增强具有不同锐化强度的给定图像，其中使用加权非平稳滤波器组合不同增强的图像。为了进行评估，引入了新的视觉投影评估 (VPA) 数据集以及用于量化运动伪影的新指标。