Analysis and design of coded apertures for defocus deblurring based on imaging system properties and optical features

Abstract

As the physical size of single pixels in digital cameras grows smaller, the captured images are increasingly affected by defocused blurring and consequently valuable details are lost. Different aperture patterns have already been proposed to mitigate this problem based on presumed conditions, which maybe violated in practise. Sensor characteristics and current photometric scene properties have been largely ignored in the design of aperture patterns in the literature. In this study, a number of perceptually optimised coded apertures are introduced for defocused deblurring. These apertures are specifically designed considering illumination conditions, sensor specifications and human visual system characteristics. The designed patterns are compared with circular apertures of equal throughput and pinhole aperture. Experiments show signal-to-noise ratio (SNR) gains of up to 0.35 and 2 dB over circular and pinhole apertures, respectively. To study the trade-off between diffraction and deblurring gains, the proposed binary masks are enhanced by smoothing and morphological operations, which can yield non-binary and rounded binary patterns. The results of the authors’ study show that rounded binary patterns improve diffraction behaviour while maintaining the desired SNR level.