Multi-View Optical Image Fusion and Reconstruction for Defogging without a Prior In-Plane

Image fusion and reconstruction from muldti-images taken by distributed or mobile cameras need accurate calibration to avoid image mismatching. This calibration process becomes difficult in fog when no clear nearby reference is available. In this work, the fusion of multi-view images taken in fog by two cameras fixed on a moving platform is realized. The positions and aiming directions of the cameras are determined by taking a close visible object as a reference. One camera with a large field of view (FOV) is applied to acquire images of a short-distance object which is still visible in fog. This reference is then adopted to the calibration of the camera system to determine the positions and pointing directions at each viewpoint. The extrinsic parameter matrices are obtained with these data, which are applied for the image fusion of distant images captured by another camera beyond visibility. The experimental verification was carried out in a fog chamber and the technique is shown to be valid for imaging reconstruction in fog without a prior in-plane. The synthetic image, accumulated and averaged by ten-view images, is shown to perform potential applicability for fog removal. The enhanced structure similarity is discussed and compared in detail with conventional single-view defogging techniques.