关键词: 光场图像, 基线编辑, 图像重定向, 深度卷积神经网络

Abstract: Image retargeting is one of the fundamental problems in image editing, which studies how to rearrange image content according to various application requirements. Current research on light field image retargeting except angular and spatial super-resolution is still blank. This paper proposes a method to edit the baseline of light field images. The method mainly contains three steps. First, the method calibrates the light field image to obtain the camera parameters, and estimates the disparity maps for each subaperture view. Then the method retargets the light field image according to the baseline editing requirement, which means that all subaperture views are projected to the corresponding subaperture viewpoint of target light field image. Finally, a deep learning method is proposed to optimize the target light field images, which can well inpaint the black holes of disoccluded regions in direct retargeting process. Experimental results demonstrate that the method can perform baseline editing based light field images retargeting, and obtain visual pleasure synthesized light field image. The proposed method can be used in a wide variety of light field images processing applications, such as light field image stitching, object copy and paste in different images, stereoscopic 3D display of light field images, etc.

Key words: light field image, baseline editing, image retargeting, deep convolutional neural network