Super-resolution imaging via sparsity constraint and sparse speckle illumination

We present an imaging approach via sparsity constraint and sparse speckle illumination which can dramatically enhance the optical system's imaging resolution. When the object is illuminated by some sparse speckles and the sparse reconstruction algorithm is utilized to restore the blur image, numerical simulated results demonstrate that the image, whose resolution exceeds the Rayleigh limit, can be stably reconstructed even if the detection signal-to-noise ratio (SNR) is less than 10 dB. Factors affecting the quality of the reconstructed image, such as the coded pattern's sparsity and the detection SNR, are also studied.