Texture Aware Learning-based Image Fusion Method for Fixed Focal-length Cameras

摘要

This paper aims to develop a novel approach of image fusion for an asymmetrical camera system when multiple images are acquired with cameras which have large differences in focal lengths but similar sensor size with an overlapping field of view. The fused image usually becomes perceptually unpleasant because the high-frequency components of a wide-view image will be quite inadequate comparing to the tele-view images. Four steps are consisted in the proposed work: (ⅰ) image upscaling of the wide-view image, (ⅱ) texture identification on the upscaled image, (ⅲ) the performance evaluation of image upscaling, and (ⅳ) the image inpainting for the high-frequency components of the wide-view image. The field of view of tele-view camera is set to be 4 times smaller than the wide-view camera in spatial angle in the experiment. The experiment result illustrates that the proposed algorithm brings significantly perceptual improvement to the wide-view image.