DocumentCode :
60605
Title :
MMSE Design of Time and Color Multiplexing Codes
Author :
Tsung-Han Chan ; Kui Jia ; Wycoff, Eliot ; Yi Ma
Author_Institution :
Adv. Digital Sci. Center, Singapore, Singapore
Volume :
62
Issue :
5
fYear :
2014
fDate :
1-Mar-14
Firstpage :
1157
Lastpage :
1170
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 M to be equal to the number of illumination sources N. 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 KM ≥ N, where K 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 M increases. Experiments also demonstrate the effectiveness and superiority of the proposed method in illuminating various objects.
Keywords :
channel coding; convex programming; least mean squares methods; mathematical programming; multiplexing; optical communication; search problems; 1D exhaustive search; MMSE design; color channels; color multiplexing codes; computer simulations; computer vision; convex programming; graphics applications; illumination multiplexing method; illumination sources; image quality; maximum SNR approach; maximum signal-to-noise ratio; minimum mean square errors; nonconvex problem; optical multiplexing; photon noise; saturation; sequential semidefinite programming; time multiplexing codes; Image color analysis; Licenses; Light sources; Lighting; Multiplexing; Signal to noise ratio; Optical multiplexing; maximum signal-to-noise ratio (SNR); minimum mean square error (MMSE); sequential convex approximation; time and color;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2014.2300032
Filename :
6712149
Link To Document :
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