Image Restoration In Optical Sparse Aperture Systems

Constructed from multiple, identical, circular sub-apertures, optical sparse aperture imaging system is capable of producing high resolution images as same as a fully-filled one. It simultaneously reduces the cost and difficulty of manufacture. However, the sparse arrangement of sub-apertures results in attenuation of modulation transfer function (MTF) and makes MTF drop to zero value within the mid-frequency spectrum. Besides, the decreased light collection area results in severe degradation of signal to noise ratio (SNR), and the imaging environment also can bring in some disturbances, so that the output image will have a poor quality. Therefore, image restoration methods should be employed to improve the quality of output degraded image. Based on the imaging process, image restoration technology constructs mathematical model and estimates original image along its inverse direction for further processing.In this paper, firstly image degradation model of optical sparse aperture imaging system was constructed. The principle of imaging and the characteristic parameters were studied. According to the nature of two-dimensional MTF in sparse aperture arrays, a method termed as characteristic triangle was proposed to calculate the minimum fill factor, which was then successfully used in typical sparse aperture arrays such as Golay3, Golay6, Ring6 and Tri-arm7.In addition, the MTF expressions of typical sparse aperture arrays were deduced. The optical factors which affect imaging quality were analyzed. With small fill factor, the MTF nature was researched, and using Matlab software, imaging experiments were simulated under two conditions of aberration-free and aberration. More importantly, Fourier-based Deconvolution, Local Polynomial Approximation-Intersect Confidence Intervals (LPA-ICI) and Wavelet Denoise after Laplacian-Regularized Deconvolution (WDALRD) were studied and matched to optical sparse aperture imaging system. Normalized average MTF from mid-frequency to cut-off frequency was proposed as evaluation metrics.Finally, numerical simulation experiment and hardware-in-the-loop experiment were carried out to examine the performance of restorations. The results show that WDALRD can be well applied to optical sparse aperture imaging system and its estimate is the most satisfactory: textures and edges are well preserved and sharp, while the homogeneous regions are noise free.