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Optimal Daltonization by Spectral Shift for Dichromatic Vision

机译:通过光谱转变进行多层差异的最佳道顿化

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This paper proposes a spectral-based image daltonization algorithm for the dichromats getting the best visibility against their color deficiencies. The proposed model extracts the visible and invisible spectra to dichromatic vsion based on the projection theory of spectral space to/from 2-D dichromatic cone space.. First, the fundamental spectra C* visible to the trichromats are captured from the conventional sRGB camera images by a pseudo-inverse projection..Second, the fundamental spectra C*_(DIC) visible to the dichromats are obtained by operating the extended matrix R_(DIC) based on matrix-R theory. Thirdly, the lost spectra ΔC_(DIC) are calculated as the difference between C* and C*_(DIC). The key point in this paper is to make use of the lost spectra for image daltonization revived again. Though the lost spectra ΔC_(DIC) are invisible to dichromats if left alone, they are shifted into the visible spectral region and added to the the fundamental spectra C* of source image. As a result, the dichromatic image visibility is dramatically improved. The optimal spectral shift is determined to maximizing the spectral visibility for the dichromats and minimizing the visual gap from the normals. The proposed algorithm is designed to solve a contradictory demand to cope with both dichromats and normals. The paper shows how the model works well for image daltonization better than the existing popular color blind simulators.
机译:本文提出了一种基于频谱的图像Daltonization算法,用于抵抗其颜色缺陷的最佳可视性。该模型基于频谱空间的投影理论从2-D二色锥形空间的投影理论提取可见光和无形的光谱到二色V型。首先,从传统的SRGB相机图像捕获TrichRomats的基本光谱C *。通过伪逆projection..Second,基波谱C * _(DIC)的二色可见通过操作基于矩阵-R理论扩展矩阵R_(DIC)获得。第三,丢失的光谱ΔC_(DIC)被计算为C *和C * _(DIC)之间的差异。本文的关键点是利用丢失的图像Daltonization再次恢复。尽管失去了光谱ΔC_(DIC)是不可见的,如果单独留下二色,它们被转移到可见光谱区,并添加到基本光谱C *源图像。结果,显着改善了二色图像可视性。确定最佳光谱移位以最大化二分罗马的光谱可见度,并最小化来自正常的视觉间隙。所提出的算法旨在解决应对二分汉族和法线的矛盾需求。本文展示了模型如何适用于图像道顿优于现有流行的色彩盲模拟器。

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