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人类对非文字图像的感知性能:区域识别与基于纹理的分割

Human perceptual performance with nonliteral imagery: region recognition and texture-based segmentation.

作者信息

Essock Edward A, Sinai Michael J, DeFord Kevin, Hansen Bruce C, Srinivasan Narayanan

机构信息

Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY 40292, USA.

出版信息

J Exp Psychol Appl. 2004 Jun;10(2):97-110. doi: 10.1037/1076-898X.10.2.97.

Abstract

In this study the authors address the issue of how the perceptual usefulness of nonliteral imagery should be evaluated. Perceptual performance with nonliteral imagery of natural scenes obtained at night from infrared and image-intensified sensors and from multisensor fusion methods was assessed to relate performance on 2 basic perceptual tasks to fundamental characteristics of the imagery. Specifically, single-sensor imagery and fused multisensor imagery (both achromatic and false color) were used to test performance on a region recognition task and a texture segmentation task. Results indicate that the use of color rendering and type of scene content play specific roles in determining perceptual performance allowed by nonliteral imagery. The authors argue that the usefulness of various image-rendering methods should be evaluated with respect to multiple perceptual tasks.

摘要

在本研究中,作者探讨了应如何评估非文字图像的感知有用性这一问题。评估了从红外和图像增强传感器以及多传感器融合方法在夜间获取的自然场景非文字图像的感知性能,以将两项基本感知任务的性能与图像的基本特征相关联。具体而言,使用单传感器图像和融合多传感器图像(包括消色差和假彩色)来测试区域识别任务和纹理分割任务的性能。结果表明,色彩渲染的使用和场景内容类型在确定非文字图像所允许的感知性能方面发挥着特定作用。作者认为,应针对多项感知任务评估各种图像渲染方法的有用性。

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