Light Field All-in-focus Image Fusion Based on Edge Enhanced Guided Filtering

Affected by the micro-lens geometric calibration accuracy of the light field camera, the decoding error of the 4D light field in the angular direction will cause the edge information loss of the integrated refocused image, which will reduce the accuracy of the all-in-focus image fusion. In this paper, a light field all-in-focus image fusion algorithm based on edge-enhanced guided filtering is proposed. Through multi-scale decomposition of the digital refocused images and guided filtering optimization of the feature layer decision map, the final all-in-focus image is obtained. Compared with the traditional fusion algorithm, the edge information loss caused by the 4D light field calibration error is compensated in the presented method. In the step of multi-scale decomposition of the refocused image, the edge layer extraction is added to accomplish the high-frequency information enhancement. Then the multi-scale evaluation model is established to optimize the edge layer's guided filtering parameters to obtain a better light field all-in-focus image. The experimental results show that the edge intensity and the perceptual sharpness of the all-in-focus image can be improved without significantly reducing the similarity between the all-in-focus image and the original image.