Model-Based Image Enhancement for the Visually Impaired

描述(申请人提供)：视频图像的增强应使视障人士更容易获得电视和其他视频来源。前些年，基于带通滤波的对比度增强和宽带增强方法被开发和测试。结果是令人鼓舞的，显示出在人脸识别和从运动视频中获取细节方面的改进，以及对静态和运动视频中增强图像的适度偏好。我们认为，对增强图像的适度偏好是对增强图像的短期适应的结果，这是最近一些实验室报告的效果。我们将调查这些适应效应，包括中心视野丧失患者的适应效应，并将测试旨在克服这些影响的增强方法。此外，我们将继续评估宽带增强和基于mpeg的增强的改进版本，这两者也可以从相同的反自适应方法中受益。 这项研究的基本视觉建模方面将检查在长期中心视觉丧失的外围视觉处理过程中发生的变化和适应。特别是，视力受损患者的远程促进研究将被用于寻找视觉功能的测量方法，以解释和量化外围视网膜的模式视觉缺陷。在上一次赠款期间开始的视力时间方面的研究将继续并扩大。基础研究的结果将指导视觉模型的进一步完善，以及增强技术的调整和优化。 通过对基于视频的图像进行图像增强，我们期望提高视力障碍者的生活质量。

DESCRIPTION (provided by applicant): Enhancement of video images should enable visually impaired people greater access to TV and other video sources. In previous years, contrast enhancement based on band-pass filtering and wide-band enhancement approaches were developed and tested. Results were encouraging, showing improved performance in face recognition and in obtaining details from motion videos as well as modest preference for enhanced images in both static and motion video. We believe that the modest level of preference for enhancement was a result of short-term adaptation to enhanced images, an effect that was recently reported from a number of labs. We will investigate these adaptation effects, including those in patients with central field loss, and will test enhancement methods that aim to overcome these effects. Also, we will continue evaluation of improved versions of the wide-band enhancement and the MPEG-based enhancement, both of which could benefit also from the same counter-adaptive approaches. The basic vision modeling aspect of the study will examine changes and adaptations that occur in peripheral vision processing with long-term central visual loss. In particular, studies of long-range facilitation in visually-impaired patients will be used in a search for measures of visual function that will explain and quantify deficits in pattern vision in peripheral retina. Studies of temporal aspects of vision started in the last grant period will be continued and expanded. Results of basic studies will guide further refinement of the visual model, and tuning and optimization of the enhancement techniques. Through image enhancement of video-based images, we expect to improve the quality of life of people with visual impairments.