CORRECTION OF SATURATED REGIONS IN RGB COLOR SPACE

Q4 Mathematics
Hae Jin Ju, Rae-Hong Park
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引用次数: 2

Abstract

In a digital image, color representation of a digital image sensor is limited to a narrow dynamic range. Especially, when extremely bright light is captured, the original color of a scene is saturated to the maximum value, up to which a digital image sensor can represent the color. This paper proposes an algorithm that corrects the color in a saturated region, where the original color is distorted and lost. For natural correction, i.e., to minimize the artifacts near the boundary of a saturated region, the proposed method uses the weighted sum of color value(s) in the saturated color channel(s) of neighborhood of saturated regions. In determining the weight of each pixel, saturation, hue, and color values are used with the certainty map. Using the certainty map, the proposed method can reliably distinguish the unsaturated and already desaturated neighboring pixels from the remaining pixels. Then, the proposed correction method computes the weight function using saturation, hue, and color values. Therefore, the proposed algorithm can get reliable corrected colors. Comparison of experimental results of the proposed and existing correction methods shows the effectiveness of the proposed saturated region correction method in the view of natural color restoration.
RGB色彩空间中饱和区域的校正
在数字图像中,数字图像传感器的颜色表示受限于一个狭窄的动态范围。特别是,当捕捉到非常明亮的光线时,场景的原始颜色被饱和到最大值,数字图像传感器可以表示该颜色。本文提出了一种校正饱和区域中原始颜色失真和丢失的算法。对于自然校正,即为了最小化饱和区域边界附近的伪影,提出的方法使用饱和区域邻域的饱和颜色通道中颜色值的加权和。在确定每个像素的权重时,饱和度、色调和颜色值与确定性图一起使用。利用确定性映射,该方法可以可靠地从剩余像素中区分出不饱和和已经去饱和的相邻像素。然后,提出的校正方法使用饱和度、色调和颜色值计算权重函数。因此,该算法可以得到可靠的校正颜色。将所提校正方法与现有校正方法的实验结果进行了比较,结果表明所提饱和区域校正方法在自然色彩恢复方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
4
审稿时长
>12 weeks
期刊介绍: The International Journal of Computational Geometry & Applications (IJCGA) is a quarterly journal devoted to the field of computational geometry within the framework of design and analysis of algorithms. Emphasis is placed on the computational aspects of geometric problems that arise in various fields of science and engineering including computer-aided geometry design (CAGD), computer graphics, constructive solid geometry (CSG), operations research, pattern recognition, robotics, solid modelling, VLSI routing/layout, and others. Research contributions ranging from theoretical results in algorithm design — sequential or parallel, probabilistic or randomized algorithms — to applications in the above-mentioned areas are welcome. Research findings or experiences in the implementations of geometric algorithms, such as numerical stability, and papers with a geometric flavour related to algorithms or the application areas of computational geometry are also welcome.
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