Multichannel vision system for estimating surface and illumination functions

Tominaga, Shoji

doi:10.1364/josaa.13.002163

Cited by 130 publications

(58 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Linear finite-dimensional models [6,7] will be used to describe the surface spectral-reflectance vector of an imaged object. Specifically, suppose that a close approximation of f,f, can be exactly expressed as a linear combination of M basis functionsf = Fd (2) where F is an N M matrix whose columns contain the basis functions that describe most of the reflectance spectra in a training dataset, and d is the M-element vector which represents the weights of the linear expansion (2).…”

Section: Mathematical Definitionsmentioning

confidence: 99%

See 1 more Smart Citation

Color constancy from multispectral images

Abrardo

Alparone²,

Cappellini³

et al.

Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348)

View full text Add to dashboard Cite

This paper describes a computational method for estimating the body reflectance function of color surfaces. The experimental apparatus consists of a vision system having seven spectral channels whose wavelength sensitivities cover the visible spectrum. The estimation of the spectral-reflectance function is based on finite-dimensional linear models. In order to use digitized imaged data to evaluate the surface reflectance, a procedure for bypassing the problem of unknown illuminant spectral-power distribution was devised. For the simple objects used (color checker charts), it is found that an accuracy greater than 97% can be achieved.

show abstract

Section: Mathematical Definitionsmentioning

confidence: 99%

“…A classical approach to color constancy is the finitedimensional linear model [5,6,7]. Such a method conveys all spectral information into few numbers, supposing that illumination and reflectance can be approximated each by a weighted sum of basis functions.…”

Section: Introductionmentioning

confidence: 99%

Color constancy from multispectral images

Abrardo

Alparone²,

Cappellini³

et al.

Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348)

View full text Add to dashboard Cite

show abstract

“…Although many algorithms were proposed for scene illuminant estimation, most algorithms assumed spatially uniform illumination from a single light source [30,31]. Concerning spectral imaging, we presented an illuminant estimation method from the outputs of a multi-channel vision system [26,30], where the dichromatic reflection model was assumed to object surfaces. Therefore the illuminant spectrum could be estimated from the interface reflection component.…”

Section: Illumination Estimation and Invariant Representationmentioning

confidence: 99%

Invariant representation for spectral reflectance images and its application

Ibrahim

Tominaga

Horiuchi

2011

J Image Video Proc.

Self Cite

View full text Add to dashboard Cite

Spectral images as well as color images observed from object surfaces are much influenced by various illumination conditions such as shading and specular highlight. Several invariant representations were proposed for these conditions using the standard dichromatic reflection model of dielectric materials. However, these representations are inadequate for other materials like metal. This article proposes an invariant representation that is derived from the standard dichromatic reflection model for dielectric and the extended dichromatic reflection model for metal. We show that a normalized surface-spectral reflectance by the minimum reflectance is invariant to highlights, shading, surface geometry, and illumination intensity. Here the illumination spectrum and the spectral sensitivity functions of the imaging system are measured in a separate way. As an application of the proposed invariant representation, a segmentation algorithm based on the proposed representation is presented for effectively segmenting spectral images of natural scenes and bare circuit boards.

show abstract

“…Although several types of multiband camera systems in the field of still imaging have been developed, [1][2][3][4][5][6][7][8] most of them are multi-shot-type systems, such as a monochrome camera with a rotating filter wheel, and they cannot take images of moving objects. Ohsawa et al…”

Section: Introductionmentioning

confidence: 99%

Stereo one-shot six-band camera system for accurate color reproduction

Tsuchida

Sakai

Miura

et al. 2013

J. Electron. Imaging

View full text Add to dashboard Cite

Abstract. For accurate color reproduction of motion pictures or still pictures of moving objects, we developed a different one-shot sixband image-capturing and visualization system that combines multiband and stereo imaging techniques. The proposed system consists of two consumer-model digital cameras and an interference filter whose spectral transmittance is comb-shaped. Subpixel correspondence search between the stereo image pairs is conducted and image transformation whose parameters are estimated from the correspondence is used to correct the geometric relationship between the images. The Wiener estimation method is used for color reproduction. For experiments, we have constructed two six-band camera systems to evaluate the quality of resultant images. One is for capturing high-resolution images using digital single-lens reflex cameras. The other is for capturing motion pictures using digital video cameras, for which all image processing steps after image capture are implemented on graphics processing units and the frame rate of the system is 30 fps when image size is XGA. For both systems, the average color difference between the measurement data and estimation results for 24 color patches of the Macbeth ColorChecker™ is dEa Ã b Ã ¼ 1.21 at maximum.

show abstract

Multichannel vision system for estimating surface and illumination functions

Cited by 130 publications

References 15 publications

Color constancy from multispectral images

Color constancy from multispectral images

Invariant representation for spectral reflectance images and its application

Stereo one-shot six-band camera system for accurate color reproduction

Contact Info

Product

Resources

About