Bilinear interpolation algorithm based on gradient-weighted optimization

To address the problems of instantaneous field of view (IFoV) error and blurred details of infrared division of focal plane (DoFP) polarization images, this paper proposes a Bilinear interpolation algorithm based on gradient-weight optimization. The improvement of the algorithm mainly involves the following aspects: (1) the interpolation image pixels are extended for the characteristics of infrared DoFP polarization images, and the gradient correlation between the image elements is effectively used, to improve the interpolation accuracy; (2) the weighting factor is introduced to reconstruct the image pixels with weighting ratios, which improves the self-adaptive ability of the algorithm. The experimental results show that the algorithm in this paper effectively solves the problem of IFoV error of infrared polarization images, significantly enhances the contrast and sharpness of the degree of polarization images and meet the real-time hardware processing requirements. Experimental results showed that the PSNR of light intensity image increased by 4.4949dB, 3.5762dB and 1.5059dB compared with Nearest, Bilinear and Bicubic algorithms; the PSNR of the degree of polarization image by improved interpolation algorithm in this paper was increased by 2.3652dB, 2.2304dB and 2.0945dB, and the SSIM was increased by 0.0824, 0.1131 and 0.0881, compared with the Nearest, Bilinear and Bicubic algorithms; the operation speed of polarization image by improved interpolation algorithm in this paper was increased by 19.57fps and 21.68fps compared with Bicubic convolution and Gaussian interpolation algorithms.