Omni-total variation algorithm for the restoration of all-focused catadioptric image

Abstract

In this paper, we present a novel omni-total variation (Omni-TV) algorithm for the restoration of defocus blur to obtain all-focused catadioptric image. Catadioptric omni-directional imaging systems usually consist of conventional cameras and curved mirrors for capturing 360° field of view. Mirror curvature in the catadioptric camera often leads to noticeable blurring artifacts in omni-directional imaging. The problem becomes more severe when high resolution sensor is introduced. In an omni-directional image, two points near each other may not be close to one another in the 3D scene. Traditional gradient computation cannot be directly applied to omni-directional image processing. Thus, an omni-gradient computing method combined with the characteristics of catadioptric imaging is proposed, in which an Omni-TV minimization is used as the constraint for deconvolution regularization. The proposed method is vital for improving catadioptric omni-directional imaging quality and promoting applications in related fields like omni-directional video and image processing.