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Spatial Gamut Mapping based on Guided Filter to Preserve Spatial Luminance Variation

机译:基于导引滤波器的空间色域映射可保留空间亮度变化

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In this article, a spatial gamut mapping algorithm (SGMA) based on the guided filter is proposed. In this SGMA, the guided filter is firstly used to decompose the luminance channel of input image into high-pass signal representing image details (or textures) and low-pass signal representing image edges (or contours). The low-pass luminance signal is combined with other channels (chroma and hue) to get base-layer image. After the gamut mapping of base-layer image, the enhanced high-pass luminance signal is added back to the gamut-mapped base-layer image for detail preservation. Finally, the detail-preserved image is mapped to the destination gamut once again. In this article, the properties of the proposed SGMA, which include the principle of the guided filter, the influences of different guidance images on gamut mapping results, the influences of different frequency-band-decomposition methods on gamut mapping results, and the influences of different guided-filtering parameters on detail preservation, are analyzed in detail. The results of psychophysical experiments indicate that the proposed SGMA is better at detail preservation than pointwise GMAs, and has good performance on preference and reproduction accuracy. More importantly, the halos-testing experimental results verify the advantage of the proposed SGMA in avoiding halo-artifacts. (C) 2017 Society for Imaging Science and Technology.
机译:本文提出了一种基于导引滤波器的空间色域映射算法(SGMA)。在该SGMA中,首先使用导引滤波器将输入图像的亮度通道分解为代表图像细节(或纹理)的高通信号和代表图像边缘(或轮廓)的低通信号。低通亮度信号与其他通道(色度和色相)组合以获得基本层图像。在基层图像的色域映射之后,将增强的高通亮度信号添加回色域映射的基层图像,以保留细节。最后,保留细节的图像再次映射到目标色域。本文提出的SGMA的特性包括:导引滤波器的原理,不同导引图像对色域映射结果的影响,不同的频带分解方法对色域映射结果的影响以及详细分析了细节保存中的不同引导过滤参数。心理物理实验结果表明,所提出的SGMA比逐点GMA具有更好的细节保存能力,并且在偏好和复制精度上都有良好的表现。更重要的是,光晕测试实验结果验证了所提出的SGMA在避免光晕伪像方面的优势。 (C)2017年影像科学与技术学会。

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