摘要翻译：
多光谱成像技术在许多领域得到了广泛的应用，但获取和存储图像数据的成本仍然很高。带有多光谱滤光片阵列的单传感器相机可以以略低的图像质量为代价，降低捕捉图像的成本。当采用多光谱滤波器阵列时，插值后可以应用传统的多光谱图像压缩方法，但由于插值后的压缩图像数据是从捕获的原始数据中计算出来的，因此插值后的压缩图像数据具有一定的冗余性。本文针对单传感器多光谱相机，提出了一种高效的图像压缩方法。提出的方法在插值前对捕获的多光谱数据进行编码。我们还提出了一种新的用于拼接多光谱图像压缩的光谱变换方法。该变换是在考虑滤波器排列和多光谱滤波器阵列的光谱灵敏度的基础上设计的。实验结果表明，该方法在更高的比特率下比传统的多光谱图像插值压缩方法获得了更高的峰值信噪比，如在0.1比特/像素/波段以上的编码速率下比传统的压缩方法获得了3-dB的增益。
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英文标题：
《Mosaicked multispectral image compression based on inter- and intra-band
  correlation》
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作者：
Kazuma Shinoda, Madoka Hasegawa, Masahiro Yamaguchi, Antonio Ortega
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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英文摘要：
  Multispectral imaging has been utilized in many fields, but the cost of capturing and storing image data is still high. Single-sensor cameras with multispectral filter arrays can reduce the cost of capturing images at the expense of slightly lower image quality. When multispectral filter arrays are used, conventional multispectral image compression methods can be applied after interpolation, but the compressed image data after interpolation has some redundancy because the interpolated data are computed from the captured raw data. In this paper, we propose an efficient image compression method for single-sensor multispectral cameras. The proposed method encodes the captured multispectral data before interpolation. We also propose a new spectral transform method for the compression of mosaicked multispectral images. This transform is designed by considering the filter arrangement and the spectral sensitivities of a multispectral filter array. The experimental results show that the proposed method achieves a higher peak signal-to-noise ratio at higher bit rates than a conventional compression method that encodes a multispectral image after interpolation, e.g., 3-dB gain over conventional compression when coding at rates of over 0.1 bit/pixel/bands.
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PDF链接：
https://arxiv.org/pdf/1801.03577