人类视觉系统中凸点状态识别

Bharath, N. Jeba, P. Priyadharshini, Gurur raja
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引用次数: 0

摘要

人类视觉系统(HVS)在水平方向上寻找选择相关区域的方法尝试。视觉集中的努力,猜测电影或图像的基本区域,通过个人的眼睛观察。这样的表示,适用于类似工作站工作、MPEG惯例和卓越性评估的领域。虽然预计会有许多模型,但其中只有一些与高动态范围(HDR)图像实体相关,此外还没有完成HDR可视化的工作。此外,可获得形式内部的缺点是,它们无法在HDR物质中建立的广泛发光阵列下再现HVS的独特性。本文采用过程方法,通过合并图像的时空特征来表示HDR输入的自底向上的视觉显著性,从而克服了这些问题。通过对人眼眼球运动信息的检验,验证了该模型的有效性。使用3个众所周知的定量指标进行评估表明,所提出的模型明显更好地预测了HDR物质的视觉浓度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Protuberancy State Recognition in Human Visual System
The human visual system (HVS) seeks toward select relevant region in the direction of level rear method attempts. visual concentration effort to guess the essential region of films or imagery observed through an individual eye. Such representations, are functioned to areas similar to workstation work, MPEG conventions, and an eminence evaluation. while numerous models are expected, only some of them be pertinent enroute for high dynamic range (HDR) picture substance, in addition to no effort has been completed for HDR visualization. Furthermore, the disadvantage inside the obtainable form is with the intention, they couldn't reproduce the uniqueness of HVS beneath the extensive shining array established in HDR substance. This paper gets the better of these troubles by the process approach to represent the bottom-up visual saliency for HDR input through merge spatial and temporal image features. An examine of a human eye ball movement information make sure the efficiency of the proposed model. Evaluation using 3 well-known quantitative metrics show that the proposed model significantly gets better predictions of visual concentration for HDR substance.
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