Multiplexed fluorescence unmixing

Alterman, Marina; Schechner, Yoav Y.; Weiss, Aryeh

doi:10.1109/iccphot.2010.5585093

Cited by 24 publications

(29 citation statements)

References 35 publications

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“…In such a case, the unique solution of the demultiplexing matrix can be easily determined to be , as and are both square. Hence, problem (11) can be further simplified to (12) Clearly, the above problem minimizes the sum of the noise power in (from (5)) or, equivalently, maximizes its signal-to-noise ratio (SNR). Problem (12) originates from a constrained MMSE formulation, but to differentiate the general MMSE design (9), we name this instance as the maximum-SNR design.…”

Section: Background Of Time Multiplexingmentioning

confidence: 99%

“…Problem (9) is a difficult non-convex problem. Early efforts [1], [2], [4], [10]- [12] primarily focused on handling the MMSE problem (9) with the added constraint of :…”

Section: Background Of Time Multiplexingmentioning

confidence: 99%

“…Alterman et al [12] relaxed the limitation that for max-SNR multiplexing for multiplexed fluorescence unmixing, but their problem design additionally has to take into account the natural mixing in fluorescent images, which does not fall into the scope of this paper. Moreover, many existing works have utilized time and color multi-plexing for various purposes, for instance: [4] employing cyan, magenta and yellow patterns for the illumination of the faces of mannequins; [13] using a cluster of light sources with different spectra and an RGB camera for multispectral imaging; [14] extending time multiplexing with color multiplexing for the capture of dynamic scenes; and [6] utilizing time and color multiplexing for dynamic photometric stereo.…”

Section: Introductionmentioning

confidence: 99%

“…• We provide a new MMSE criterion formulation, under which the conventional max-SNR approach [1], [2], [4], [10]- [12] is viewed as a constrained MMSE problem. • The MMSE-based formulated problem is more general and more difficult than the max-SNR problem [15].…”

Section: Introductionmentioning

confidence: 99%

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MMSE Design of Time and Color Multiplexing Codes

Chan

Jia

Wycoff

et al. 2014

IEEE Trans. Signal Process.

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Abstract-Illumination multiplexing has proven itself to be a valuable tool in image quality improvement for many computer vision and graphics applications, provided that its limitations on photon noise and saturation are properly tackled. Currently, multiplexing codes are constructed according to the maximum signal-to-noise ratio (SNR), and they are primarily employed for time multiplexing, a technique that requires the number of measurements to be equal to the number of illumination sources . In this work, we propose an illumination multiplexing method based on minimum mean square errors (MMSEs) for the more general setting of both time and color multiplexing performed together, with , where is the number of color channels. Under the umbrella of the proposed MMSE formulation, the conventional maximum SNR approach can be thought of as a special case of the MMSE design. The formulated MMSE problem is a difficult non-convex problem, but it can be approximated by sequential semi-definite (convex) programming and a 1-D exhaustive search. The proposed formulation and algorithm can be readily specialized to max-SNR and/or time multiplexing designs, thereby giving the optimized codes a much broader scope of application. Computer simulations show that the conventional max-SNR design is suboptimal to the proposed MMSE design, though both see significant quality improvements as increases. Experiments also demonstrate the effectiveness and superiority of the proposed method in illuminating various objects.Index Terms-Optical multiplexing, maximum signal-to-noise ratio (SNR), minimum mean square error (MMSE), sequential convex approximation, time and color.

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Section: Background Of Time Multiplexingmentioning

confidence: 99%

“…Problem (9) is a difficult non-convex problem. Early efforts [1], [2], [4], [10]- [12] primarily focused on handling the MMSE problem (9) with the added constraint of :…”

Section: Background Of Time Multiplexingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MMSE Design of Time and Color Multiplexing Codes

Chan

Jia

Wycoff

et al. 2014

IEEE Trans. Signal Process.

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show abstract

“…An analogous multiplexing concept has been brought into the domain of computer vision and graphics by Schechner et al in 2003 [2], where they illuminated objects by multiple sources from different directions and computationally demultiplexed the received images, attempting to acquire high-SNR, single-light source images. Such a multiplexing scheme was afterwards employed in applications, such as scene recovery [3], object relighting [4], fluorescence unmixing [5] and photometric stereo [6][7][8], and has been proved to improve SNR.…”

Section: Introductionmentioning

confidence: 99%

Towards Optimal Design of Time and Color Multiplexing Codes

Chan

Jia

Wycoff

et al. 2012

Computer Vision – ECCV 2012

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Abstract. Multiplexed illumination has been proved to be valuable and beneficial, in terms of noise reduction, in wide applications of computer vision and graphics, provided that the limitations of photon noise and saturation are properly tackled. Existing optimal multiplexing codes, in the sense of maximum signal-to-noise ratio (SNR), are primarily designed for time multiplexing, but they only apply to a multiplexing system requiring the number of measurements (M ) equal to the number of illumination sources (N ). In this paper, we formulate a general code design problem, where M ≥ N , for time and color multiplexing, and develop a sequential semi-definite programming to deal with the formulated optimization problem. The proposed formulation and method can be readily specialized to time multiplexing, thereby making such optimized codes have a much broader application. Computer simulations will discover the main merit of the method-a significant boost of SNR as M increases. Experiments will also be presented to demonstrate the effectiveness and superiority of the method in object illumination.

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Multiplexed Illumination

Alterman¹

2014

Computer Vision

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Multiplexed fluorescence unmixing

Cited by 24 publications

References 35 publications

MMSE Design of Time and Color Multiplexing Codes

MMSE Design of Time and Color Multiplexing Codes

Towards Optimal Design of Time and Color Multiplexing Codes

Multiplexed Illumination

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