We have theoretically investigated the reflectivity spectrums of single- and double-layer photonic crystal slabs and the dielectric multilayer stack. It is shown that light can be perfectly confined in a single-layer photonic crystal slab at a given incident angle by changing the thickness, permittivity or hole radius of the structure. With a tunable double-layer photonic crystal slab, we demonstrate that the occurrence of tunable bound states in the continuum is dependent on the spacing between two slabs. Moreover, by analytically investigating the Drude lossless multilayer stack model, the spacing dependence of bound states in the continuum is characterized as the phase matching condition that illuminates these states can occur at any nonzero incident angles by adjusting the spacing.

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Computational imaging makes it possible to reconstruct hidden objects through random media and around corners, which is of fundamental importance in various fields. Despite recent advances, computational imaging has not been studied in certain types of random scenarios, such as tortuous corridors filled with random media. We refer to this category of complex environment as a ’random corridor’, and propose a reduced spatial- and ensemble-speckle intensity correlation (RSESIC) method to image a moving object obscured by a random corridor. Experimental results show that the method can reconstruct the image of a centimeter-sized hidden object with a sub-millimeter resolution by a low-cost digital camera. The imaging capability depends on three system parameters and can be characterized by the correlation fidelity (CF). Furthermore, the RSESIC method is able to recover the image of objects even for a single pixel containing the contribution of about 102 speckle grains, which overcomes the theoretical limitation of traditional speckle imaging methods. Last but not least, when the power attenuation of speckle intensity leads to serious deterioration of CF, the image of hidden objects can still be reconstructed by the corrected intensity correlation.

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