一种双引导滤波的光场去马赛克方法

A light field demosaicing method with double guided filtering

针对光场相机特定透镜结构及透镜边缘像素混叠导致获得的光场多视角图像质量较差的问题,本文提出了一种基于双引导滤波的光场去马赛克算法。首先用白图像及透镜掩膜信息重新加权基于梯度的无阈值(GBTF)算法重建G图像,然后使用重建的G图像对R/B图像进行双引导重建R/B图像,最后将重建的R、G、B图像组合为全彩色图像。实验结果表明,与其他先进去马赛克方法相比,指标CPSNR提高1.68%,指标SSIM提高2%,并且本文方法得到的光场多视角图像具有清晰的边缘和较少的颜色伪影。

Aiming at the problem that the light field multi-view image quality is poor which is resulting from the specific lenslet structure of the light field camera and pixel aliasing at the lenslet edge, a light field demosaicing algorithm based on double-guided filtering is proposed. First, the G image is reconstructed by reweighting the gradient based threshold free(GBTF) algorithm with the white image and lenslet mask information. Then, the reconstructed G image is used to double-guide the R/B image for reconstruction. Finally, the reconstructed R, G, and B images are combined into a full color image. The demosaicing result demonstrates that compared with other advanced demosaicing algorithms, the index CPSNR is increased by 1.68%, the index SSIM is increased by 2%, and the light field multi-view image obtained by our method has clear edges and less color artifacts.