Abstract
With the development of computational photography, single-lens camera combined with corresponding image deblurring algorithm is gradually becoming a new research direction, replacing complex modern optical imaging system such as single lens reflex (SLR) camera. For single-lens camera, the Point Spread Function (PSF) estimation accuracy will directly affect the image restoration effect. In this paper, we designed the simple-lens cameras with one, two and three lenses, respectively, and propose a robust and accurate PSF estimation method of simple-lens camera. The key point of estimation is to obtain the blur image and clear image pairs, which are necessary for non-blind deconvolution PSF estimation. Considering the structure characteristic of simple-lens camera, we take picture of original clear image displayed on the computer screen to get the image pairs through corner detection and color correction is made to remove color distortion. In addition, a few studies have shown that the PSF of the simple lens is close to the spatially deformed wedge, so we use a more reasonable Normal Sinh-Arcsinh (NSAS) model to fit the blur kernel and get its parameters by Powell algorithm. The experiment results have shown that the space-variant PSF estimated by the proposed method achieves better performance than the compared methods both qualitatively and quantitatively.
Highlights
Modern optical imaging system is a trade-off between design complexity, price, volume, weight and other factors
While imaging with monochromatic light, most single lens in optical imaging system with spherical surface suffer from the following optical aberrations, such as spherical aberration, coma, astigmatism, field curvature, geometric distortions [1].While imaging with white light, chromatic aberration will exist during the imaging process because of dispersion effect
EXPERIMENTS AND RESULTS we present a number of detailed comparisons of the proposed non-blind Point Spread Function (PSF) estimation method and the state-of-the-art blind PSF estimation methods
Summary
Modern optical imaging system is a trade-off between design complexity, price, volume, weight and other factors. Schuler et al [5] proposed a method to improve the image quality of single-lens camera, which worked in YUV color space, solving the deconvolution and demosaicing problems simultaneously. Based on the study of Schuler, Heide et al [6] designed a zoom single-lens camera with focal length of 130mm and aperture of F4.5, as shown in Figure 1 (b) They first estimated the PSF of single-lens camera and proposed a non-blind deconvolution method to correct the optical aberrations which affected the image quality. They propose to use a white-noise pattern rather than regular checkerboard image or Joshi ’s arc-shaped pattern as the calibration target This method constrains the energy of the PSF by introducing a normalization prior to the PSF estimation function. Considering the design cost and lens size, our self-made simple-lenses are all C-Mount lenses with lengths of 2.0cm, 4.2cm and 3.5cm, respectively
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