Artefact‐free image stitching via a better normed seam‐cutting energy function
Xiangyan Qiu, Qiaoliang Li · IET Image Processing · 2020
Abstract Image stitching, as the important field of computer graphics and vision, has received much attention in recent years. Image stitching techniques are generally decomposed into two phases: image alignment, which aligns target images with the reference images; and image composition, which fixes ghosting and visual artefacts. This work aims to propose a new strategy for the seam‐cutting method which provides visually appealing result. Seam‐cutting is one of the most influential methods in image composition, which can relieve artefacts and produce plausible results. However, it is observed that the state‐of‐the‐art seam‐cutting approaches usually lead to undesirable seams in some challenging scenes. Here, the authors put forward a novel seam‐cutting method by defining a new energy function. This method uses power of norm as a colour difference which can magnify the weight of colour distinction to avoid undesirable seams and artefacts. The proposed method can be easily implemented. The test images are collected from the public available challenging datasets and taken by ourselves. Experiments demonstrate that the proposed method can create comparable or even better stitching results compared to other state‐of‐the‐art seam‐cutting approaches.