Molten image fusion and enhancement based on image decomposition in frequency domain

Linli Xu, Jinru Hang, Jing Han, Tian Wang, Lianfa Bai

Abstract: In this paper, we propose a novel molten image enhancement and fusion method based on image decomposition in frequency domain. The algorithm combines the guided filter to maintain the original edge and details and to make it show a more permeable visual effect. Firstly, the high-quality molten imaging band is obtained by analyzing the characteristic spectra of welding materials and arcs. We choose the bands with more spectra feature of materials and weaker arc interference as our optical path channels and collect color images at the same moment to obtain more molten information. Then, after a series of image preprocessing, we combine the details extraction strategy and the guided filter together to yield a novel fusion algorithm, which can make the fusion result to have rich information, clearer edge and higher contrast. Finally, the experimental results show that the proposed method has obvious advantages over some existing methods from the objective and the subjective view.