Spectral spaces and color spaces

Ramanath, Rajeev; Kuehni, Rolf G.; Snyder, Wesley E.; Hinks, D. G.

doi:10.1002/col.10211

Cited by 39 publications

(36 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The weights are obtained from a principal components analysis (Parkkinen et al, 1989;Vrhel et al, 1994;Maloney, 1999;Ramanath et al, 2004) with the Karhunen-Loève transform (KLT). This choice corresponds to the direction in the multichannel space having maximum variance.…”

Section: Pre-and Postprocessing Stepsmentioning

confidence: 99%

Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images

Forster

Ville

Berent

et al. 2004

Microscopy Res & Technique

346

268

View full text Add to dashboard Cite

KEY WORDSfocal range; optical microscopy; digital image processing; image fusion; complex wavelet transform ABSTRACT Microscopy imaging often suffers from limited depth-of-field. However, the specimen can be "optically sectioned" by moving the object along the optical axis. Then different areas appear in focus in different images. Extended depth-of-field is a fusion algorithm that combines those images into one single sharp composite. One promising method is based on the wavelet transform. Here, we show how the wavelet-based image fusion technique can be improved and easily extended to multichannel data. First, we propose the use of complex-valued wavelet bases, which seem to outperform traditional real-valued wavelet transforms. Second, we introduce a way to apply this technique for multichannel images that suppresses artifacts and does not introduce false colors, an important requirement for multichannel optical microscopy imaging. We evaluate our method on simulated image stacks and give results relevant to biological imaging. Microsc. Res. Tech. 65:33-42, 2004. © 2004 Wiley-Liss, Inc. INTRODUCTIONLimited depth-of-field is a common problem in biological imaging with conventional light microscopy. Often, the specimen's profile covers more than the attainable depth-of-field. Portions of the object's surface outside the optical plane appear defocused in the acquired image plane. This becomes worse as the magnification M increases because the numerical aperture NA increases, too:

show abstract

Section: Pre-and Postprocessing Stepsmentioning

confidence: 99%

Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images

Forster

Ville

Berent

et al. 2004

Microscopy Res & Technique

346

268

View full text Add to dashboard Cite

show abstract

“…33 NMF has been recently applied to the factorization of Munsell chips reflectance spectra. 34,35 In color-critical applications, spectral resemblance is very important, yet color accuracy is essential. The problem associated with all spectra decomposition methods is that they only aim to reduce the spectral misfit, without consideration of color.…”

Section: A Generalized Approach For the Choice Of Filtersmentioning

confidence: 99%

Multi‐primary design of spectrally accurate displays

Ben‐Chorin¹,

Eliav²

2007

J Soc Info Display

View full text Add to dashboard Cite

-Spectral color reproduction overcomes some inherent problems of colorimetric reproduction. An implementation of a spectral display for surface color reproduction, capable of reproducing a desired spectrum for each pixel, based on multi-primary projection technology, is presented. A light source with a spectrum identical to that of the illumination is filtered by a positive linear combination of several color filters, which reproduces the reflectance spectra. The spectra of the color filters are tailored to span the space of possible surface spectra. Various methods for choosing the color filters vis-à-vis the required performance is discussed in detail. Soft-proofing application is examined as a test case for the concept.

show abstract

“…Recently, by introducing the reduced spectral space, 10,11 it has been possible to specify the colors in terms of their principal component (PC) coordinates. The advantages/disadvantages of this space were highlighted in these papers and now, it seems possible to implement this space for the color specification and reproduction.…”

Section: Introductionmentioning

confidence: 99%

A New matching strategy: Trial of the principal component coordinates

Agahian

Amirshahi

2007

Color Research & Application

View full text Add to dashboard Cite

A new matching strategy based on the equalization of the first three principal component coordinates of sample and target in a 3D eigenvector space is stated. Two series of databases including 1269 specimens of Munsell Color Book and a virtual sample population of textile materials were selected. Their first three basis functions were extracted and considered as axes of eigenvector space. The principal component coordinates of two different collections of textile samples were determined in these spaces and considered as matching criteria. The performance of the proposed algorithm is evaluated by the color difference values under different light sources as well as the root mean square differences of reflectance curves. Results indicate some types of improvements in comparison with previous algorithms in terms of spectral as well as colorimetric accuracy.

show abstract

Spectral spaces and color spaces

Abstract: It has long been known that color experiences under con-

Cited by 39 publications

References 18 publications

Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images

Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images

Multi‐primary design of spectrally accurate displays

A New matching strategy: Trial of the principal component coordinates

Contact Info

Product

Resources

About