Interdisciplinary Program of Bioengineering, Seoul National University, Seoul 03080, Korea.
Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea.
Sensors (Basel). 2017 Oct 24;17(10):2439. doi: 10.3390/s17102439.
Most of the retinal prostheses use a head-fixed camera and a video processing unit. Some studies proposed various image processing methods to improve visual perception for patients. However, previous studies only focused on using spatial information. The present study proposes a spatiotemporal pixelization method mimicking fixational eye movements to generate stimulation images for artificial retina arrays by combining spatial and temporal information. Input images were sampled with a resolution that was four times higher than the number of pixel arrays. We subsampled this image and generated four different phosphene images. We then evaluated the recognition scores of characters by sequentially presenting phosphene images with varying pixel array sizes (6 × 6, 8 × 8 and 10 × 10) and stimulus frame rates (10 Hz, 15 Hz, 20 Hz, 30 Hz, and 60 Hz). The proposed method showed the highest recognition score at a stimulus frame rate of approximately 20 Hz. The method also significantly improved the recognition score for complex characters. This method provides a new way to increase practical resolution over restricted spatial resolution by merging the higher resolution image into high-frame time slots.
大多数视网膜假体使用头戴式摄像机和视频处理单元。一些研究提出了各种图像处理方法,以提高患者的视觉感知能力。然而,以前的研究仅侧重于利用空间信息。本研究提出了一种时空像素化方法,通过结合空间和时间信息,模拟固视眼球运动,为人工视网膜阵列生成刺激图像。输入图像以高于像素阵列数量四倍的分辨率进行采样。我们对该图像进行子采样,并生成四个不同的光幻图像。然后,我们通过依次呈现具有不同像素阵列大小(6×6、8×8 和 10×10)和刺激帧率(10 Hz、15 Hz、20 Hz、30 Hz 和 60 Hz)的光幻图像来评估字符的识别分数。在刺激帧率约为 20 Hz 时,所提出的方法显示出最高的识别分数。该方法还显著提高了复杂字符的识别分数。该方法通过将高分辨率图像合并到高帧率时隙中,为在受限的空间分辨率上提高实际分辨率提供了一种新方法。