Channel Capacity Model of Binary Encoded Structured Light-Stripe Illumination

this paper we have presented a theoretical basis for modeling and optimizing light-stripe techniques. Fig. 9. Combined encoding for determining interlace boundaries. Fig. 10. Noninterlaced ~top! and interlaced ~bottom! range images. 10 June 1998 y Vol. 37, No. 17 y APPLIED OPTICS 3695 This optimization was demonstrated through analysis of the entropy regions in stripe boundaries. Through minimization of the sampling period between high-entropy regions it is possible to attain an optimal spatial frequency while minimizing sampling error. This theory was demonstrated with a numerical light-stripe model. For validating theoretical results, experimental data were presented to demonstrate maximum frequencies and maximum lateral resolutions for our example. One can obtain further enhancements to the lateral resolution by interlacing valid regions in light structures through multiplexing. Inasmuch as the deviation of the stripe center location is typically less than the lateral spacing, interlacing achieves equivalent range resolution yet surpasses lateral sampling resolution. Therefore interlacing should permit much higher lateral resolution in most applications. Although interlacing increases the number of frames required for encoding, our research demonstrates that the system encoding rate is still significantly increased. This result has a profound effect on light-stripe methodologies, especially successive striping techniques, by permitting optimization of lateral and range measurements. Partial funding for this research was provided by NASA cooperative agreement NCCW-60 through Western Kentucky University and the Center for Manufacturing Systems, University of Kentucky. The authors thank William Chimitt for assistance in the imaging process