Photometric correction for an optical CCD-based system based on the sparsity of an eight-neighborhood gray gradient

In an optical measurement and analysis system based on a CCD, due to the existence of optical vignetting and natural vignetting, photometric distortion, in which the intensity falls off away from the image center, affects the subsequent processing and measuring precision severely. To deal with this problem, an easy and straightforward method used for photometric distortion correction is presented in this paper. This method introduces a simple polynomial fitting model of the photometric distortion function and employs a particle swarm optimization algorithm to get these model parameters by means of a minimizing eight-neighborhood gray gradient. Compared with conventional calibration methods, this method can obtain the profile information of photometric distortion from only a single common image captured by the optical CCD-based system, with no need for a uniform luminance area source used as a standard reference source and relevant optical and geometric parameters in advance. To illustrate the applicability of this method, numerical simulations and photometric distortions with different lens parameters are evaluated using this method in this paper. Moreover, the application example of temperature field correction for casting billets also demonstrates the effectiveness of this method. The experimental results show that the proposed method is able to achieve the maximum absolute error for vignetting estimation of 0.0765 and the relative error for vignetting estimation from different background images of 3.86%.