Thanks to some technical progress in interferencefilter design based on different technologies, we can finally successfully implement the concept of multispectral filter array-based sensors. This article provides the relevant state-of-the-art for multispectral imaging systems and presents the characteristics of the elements of our multispectral sensor as a case study. The spectral characteristics are based on two different spatial arrangements that distribute eight different bandpass filters in the visible and near-infrared area of the spectrum. We demonstrate that the system is viable and evaluate its performance through sensor spectral simulation.

Multispectral Filter Arrays: Recent Advances and Practical Implementation

In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The performance of the proposed adaptive Wiener estimation and the traditional method are compared in the cases of different channel numbers and noise levels. Experimental results show that the proposed method outperforms the traditional method in terms of both spectral and colorimetric prediction errors when the imaging channel number is 7 or less. When the imaging system consists of 11 or more channels, the color accuracy of the proposed method is slightly better than or becomes close to that of the traditional method.

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Reflectance reconstruction for multispectral imaging by adaptive Wiener estimation

Color is one of the most important features in digital images. The representation of color in digital form with a three-component image (RGB) is not very accurate, hence the use of a multiple-component spectral image is justified. At the moment, acquiring a spectral image is not as easy and as fast as acquiring a conventional three-component image. One answer to this problem is to use a regular digital RGB camera and estimate its RGB image into a spectral image by the Wiener estimation method, which is based on the use of a priori knowledge. In this paper, the Wiener estimation method is used to estimate the spectra of icons. The experimental results of the spectral estimation are presented.

Wiener estimation method in estimating of spectral reflectance from RGB images

Prior knowledge of the noise present in a color image acquisition device is very important in estimating colorimetric values or in recovering the spectral reflectances of pixels of objects being imaged, since these values are greatly influenced by the noise. In this paper, a new model is proposed for the determination of the noise variance of a multispectral color image acquisition system and experimental results to demonstrate its accuracy are presented. It is demonstrated that the noise variance of an actual multispectral color image acquisition system computed by the proposal agrees fairly well with the variance which minimizes the mean-square error of the recovered reflectances by the Wiener filter. As an application of the proposal, it is shown that spectral reflectances of an art painting are recovered accurately by the use of sensor responses without prior knowledge of objects being imaged and noise present in an image acquisition system.

Recovery of spectral reflectances of objects being imaged without prior knowledge

This article presents a comprehensive study on the spectrum-based color reproduction system, called Natural Vision (NV), which aims to break through the limitation of red-green-blue (RGB) three-primary schemes. After a basic discussion on the motivation for color imaging technology beyond RGB, the method for systematizing the multispectral and multiprimary color imaging technologies, including image capture, processing, storage, printing, and display is presented. Then experimental multispectral systems for both still image and video are introduced, and the following features of spectrum-based scheme are revealed: a) highly accurate color reproduction is possible even under different illumination environment, b) an expanded color gamut can be reproduced by multiprimary color displays, c) the influence of observer metamerism can be reduced by the spectral color reproduction, and d) the quantitative spectral attributes of an object, useful for its analysis or recognition, can be captured and preserved. Finally the effectiveness of the system is also demonstrated through experiments in fields of application, such as medicine, digital archives, color printing, electronic commerce, and computer graphics.

Beyond Red-Green-Blue (RGB) : Spectrum-Based Color Imaging Technology

Accurately estimating the spectral reflectance of art paintings from low-dimensional multichannel images requires that both image-acquisition hardware with appropriate spectral characteristics and appropriate estimation software be applied to the captured multichannel image. In this study, a system that incorporates both factors is designed and developed on the basis of the minimum-mean-square error criterion. The accuracy of spectral estimation by use of this system is evaluated, and the system's high performance is demonstrated.

Asako Hosoi

Papers

System design for accurately estimating the spectral reflectance of art paintings