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Poor visibility conditions due to murky water, bad weather, dust and smoke severely impede the performance of vision systems. Passive methods have been used to restore scene contrast under moderate visibility by digital post-processing. However, these methods are ineffective when the quality of acquired images is poor to begin with. In this work, we design active lighting and sensing systems for controlling light transport before image formation, and hence obtain higher quality data. First, we present a technique of polarized light striping based on combining polarization imaging and structured light striping. We show that this technique out-performs different existing illumination and sensing methodologies. Second, we present a numerical approach for computing the optimal relative sensor-source position, which results in the best quality image. Our analysis accounts for the limits imposed by sensor noise.