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Multispectral Image Compression for Color Reproduction; Weighted KLT and Adaptive Quantization based on Visual Color Perception

机译:用于色彩再现的多光谱图像压缩;基于视觉颜色感知的加权KLT和自适应量化

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An inter-band decorrelation and quantization method of multispectral data are proposed, which are suitable for lossy compression of multispectral images used for high fidelity color reproduction. The proposed inter-band decorrelation method is a modified version of Karhunen-Loeve transform (KLT), called weighted KLT (WKLT), which is designed to minimize the color difference between the color images reconstructed from original and restored multispectral images. For quantization of WKLT coefficients, adaptive quantization (AQ) is introduced in order to equalize the partiality of the perceived error which is caused by the visual nonlinearity between the luminance and the perceived lightness of the color. Through the experiments using 16-band multispectral image of an oil painting, it is confirmed that WKLT followed by AQ reduces the average and the maximum color differences in L~*a~*b~* color space in comparison with the conventional methods composed of KLT and linear quantization.
机译:提出了一种多光谱数据的频段间切片和量化方法,其适用于用于高保真颜色再现的多光谱图像的有损压缩。所提出的间间去相关方法是称为加权KLT(WKLT)的Karhunen-Loeve变换(KLT)的修改版本,其被设计为最小化从原始和恢复的多光谱图像重建的彩色图像之间的色差。为了量化WKLT系数,引入自适应量化(AQ)以均衡所感知误差的偏重率,这是由亮度和颜色的感知光照之间的视觉非线性引起的。通过使用16波段多光谱图像的油画的实验,确认WKLT随后是AQ降低了L〜* A〜* B〜*颜色空间中的平均值和最大颜色差异与由此组成的传统方法相比KLT和线性量化。

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