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基于代-线性回归模型的多光谱demosaicing用于估计伪泛色图像.

Kyeonghoon Jeong1, Sanghoon Kim1, Moon Gi Kang1

  • 1School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea.

Sensors (Basel, Switzerland)
|February 10, 2024
PubMed
概括

这项研究引入了一种新的多光谱demozaicing方法,使用通过代线性回归估计的伪泛色图像 (PPI). 这种方法提高了原始多光谱图像的空间和光谱保真度.

科学领域:

  • 计算机视觉 计算机视觉
  • 图像处理 图像处理
  • 遥感 遥感 遥感 遥感

背景情况:

  • 多光谱摄像头捕获丰富的光谱信息,但需要拆解来重建完整的空间分辨率.
  • 现有的demozaicing方法经常在多光谱图像中的光谱保真性和空间细节方面扎.

研究的目的:

  • 为多光谱图像提出一个先进的demozaicing方法.
  • 在重建的多光谱图像中提高空间和光谱的准确性.

主要方法:

  • 使用代线性回归模型估计伪泛色图像 (PPI).
  • 使用指导过 (水平和垂直) 来从子样本多谱过阵列 (MSFA) 图像中估计PPI.
  • 采用定向插值和对光谱差异的加权总和来进行demozaicing.

主要成果:

  • 与最先进的技术相比,拟议的方法显示出更高的性能.
  • 实验结果显示,合成和现实世界的多光谱图像的空间和光谱真实性得到了增强.

结论:

  • 这种新的demosaicing方法有效地重建高保真多光谱图像.
  • PPI估计和随后的插值策略显著提高了拆解精度.
关键词:
颜色demozaicing 颜色demozaicing 这是一个很好的方法.颜色插曲的色彩插曲超光谱成像技术的使用.多光谱成像技术的使用.伪泛色图像的伪泛色图像是一种伪泛色图像.

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