一种用于人工视觉弥补的计算成像模型及其评价

本文基于正在起步的人工视觉技术,在人工视觉成像模型研究以及模拟评价实验开展的基础上,提出一种基于显著性局部特征生成的像素化成像模型,并设计主观评价打分模拟实验来考察这一模型的性能.实验结果初步证实,这一模型能够向受试者优先呈现原始图像中的特征显著区域,因而使受试者主观感受到更加丰富的视觉信息.从而,该模型能够为这一新兴领域的发展提供参考.

A Computational Imaging Model and Experimental Assessment for Artificial Visual Prosthesis

The newly risen research of artificial visual prosthesis is summarized. Based on the research on the imaging model of the visual prosthesis as well as the simulated experiment, a novel imaging model based on the selection of local prominent features is proposed, and a mean-option-score-based subjective assessment is designed to evaluate the performance of the model. The results of the experiment reveal that the imaging scheme can accentuate the areas with prominent features in the original image, so as to give observers a subjective perception of rich visual information. Thus, the model will provide a new approach for future research.