The Practice of Multispectral Image Acquisition
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Multispectral imaging has been proposed as a solution to most of the problems of conventional image reproduction. The paper is focused on the practical problems of designing and operating a multispectral scanner. Several design parameters of a multispectral imaging device are discussed, including the positioning of the multispectral filters and the spectral reconstruction algorithm used during the image capture process. Finally, experimental results are given.Keywords:
Multispectral pattern recognition
Multispectral Scanner
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Multispectral images have been found useful for various applications such as remote sensing, medical imaging, military surveillance, vision inspection for food quality control, etc. but the high costs of multispectral cameras limit their usage. Low cost multispectral cameras can be developed using a single sensor multispectral filter array (MSFA) and a demosaicing method to reconstruct the complete image from under sampled multispectral image data acquired using a single sensor MSFA imaging system. In this paper, we present a new demosaicing method based on the derivative operations for the multi-spectral images. To design MSFA patterns, binary tree method is often used and the band sequence is chosen such that the middle band has a higher probability of appearance in MSFA pattern. In the proposed method, first the middle spectral band pixel values are estimated and then it is used to compute derivatives that help estimate other spectral band pixel values. Unlike many recently developed demosaicing methods that are applicable to only specific band size multispectral images, the proposed method is generic and can be applied to obtain multispectral images for any number of spectral bands. The TokyoTech dataset and CAVE dataset of multispectral images are used for the evaluation purpose, and the experimental results show that the proposed method outperforms currently best known generic multispectral demosaicing method, namely binary tree edge sensing (BTES) method on both datasets and for different band-size multispectral images.
Demosaicing
Multispectral pattern recognition
Spectral bands
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Recent algorithms developed in the field of color vision make assumptions based on the spectral reflectance curves of Munsell chips and natural materials. Some of them rely on data collected many years ago. which is partially incomplete in the visible spectrum. or contains many occurrences of the same material in it. In this article. we present a set of new measurements of different materials. In particular. we measured the spectral reflectance of Munsell chips, paints. and various natural materials in the 390–730‐nm range. In addition, we have analyzed. through principal‐component analysis, the possibility of representing the data collected with a set of basis functions. We show the implications of varying the number of principal components used (from 7 down to 3) on the errors introduced using this method.
Basis (linear algebra)
Data set
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Abstract The problem of color correction for changes in illumination is briefly reviewed. A new method using the spectral reflectance distribution in the image is introduced and compared to a white‐point mapping method. The new method is based on principal component analysis and thus is dependent upon the characteristics of the images that are to be viewed. These two methods are compared using chromaticity plots and the CIE L*a*b* ΔE measurement, for test samples which include color copiers, thermal writers, ink‐jet printers, and lithography.
Chromaticity
Spectral power distribution
Colorimetry
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Low-cost high-solution multispectral imagery is attractive to various users. This paper presents our ongoing research on developing Unmanned Airship on Board High-resolution multispectral Imaging System for quick-response to time-critical applications. First, the core component of Multispectral Imaging system is described. After that, automatic registration of collected multispectral imageries is discussed. Based on Least Square technique and classic homography principle, multi-homography model is developed to undo the motions deduced in multispectral imageries. To obtain reliable control points for the estimation of motion parameters, one FFT-induced Multispectral Imagery Matching approach is proposed as well. Next, flight experiments are implemented to collect multispectral imageries with different spatial resolution as well as imageries are registered with developed technique. Finally, conclusions and future work are conducted. Imagery usage in investigating, estimating and monitoring Miyun reservoir environment is also mentioned.
Multispectral pattern recognition
Homography
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This view of multimedia imaging places color science in a subordinate position. However, it can be worthwhile to exchange the positions. That is, multimedia imaging is but one of many technologies that exemplify color science. This approach has been described previously by the author regarding educational imperatives (1) and as a pedantic vehicle for describing the relationships between user controls and resulting color for various color technologies (2). This approach will be revisited within the context of multimedia imaging.
Imaging science
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Multispectral Scanner
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The traditional techniques of image capture, scanning, proofing, and separating do not take advantage of colorimetry and spectrophotometry. For critical color-matching applications such as catalog sales, art-book reproductions, and computer-aided design, typical images, although pleasing, are unacceptable with respect to color accuracy. The limitations that lead to these errors have a well-defined theoretical basis and are a result of current hardware and software. This has led us to a re-examination of the traditional graphic reproduction paradigm. A research and development program has begun that will alleviate the theoretical limitations associated with traditional techniques. There are four main phases: (1) Multi-spectral image capture, (2) Spectral-based separation and printing algorithm development, (3) Implementation on press, and (4) Systems integration with data and image archives. This paper describes this new paradigm, summarizes recent research results, and considers implementation opportunities.
Color management
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We propose a method for the reconstruction of the spectral reflectance function of every pixel of a fine art painting, from a series of acquisitions made through commercially available chromatic filters. We rigorously determine the minimal number of necessary filters, as well as their choice in an available set. We give the exact reconstruction formulae of the spectral reflectance functions, as well as the most adequate way to display the painting on a monitor of known colorimetric parameters.
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