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Proceedings Paper

Reconstruction of color images via Haar wavelet based on digital micromirror device
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Paper Abstract

A digital micro mirror device( DMD) is introduced to form Haar wavelet basis , projecting on the color target image by making use of structured illumination, including red, green and blue light. The light intensity signals reflected from the target image are received synchronously by the bucket detector which has no spatial resolution, converted into voltage signals and then transferred into PC[1] .To reach the aim of synchronization, several synchronization processes are added during data acquisition. In the data collection process, according to the wavelet tree structure, the locations of significant coefficients at the finer scale are predicted by comparing the coefficients sampled at the coarsest scale with the threshold. The monochrome grayscale images are obtained under red , green and blue structured illumination by using Haar wavelet inverse transform algorithm, respectively. The color fusion algorithm is carried on the three monochrome grayscale images to obtain the final color image. According to the imaging principle, the experimental demonstration device is assembled. The letter "K" and the X-rite Color Checker Passport are projected and reconstructed as target images, and the final reconstructed color images have good qualities. This article makes use of the method of Haar wavelet reconstruction, reducing the sampling rate considerably. It provides color information without compromising the resolution of the final image.

Paper Details

Date Published: 15 October 2015
PDF: 6 pages
Proc. SPIE 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology, 967437 (15 October 2015); doi: 10.1117/12.2204899
Show Author Affiliations
Xingjiong Liu, Nanjing Univ. of Science and Technology (China)
Weiji He, Nanjing Univ. of Science and Technology (China)
Guohua Gu, Nanjing Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 9674:
AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology
Haimei Gong; Nanjian Wu; Yang Ni; Weibiao Chen; Jin Lu, Editor(s)

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