An image fusion algorithm of Laplacian pyramid based on graph cuting

作者：Xiao Jin Sheng^*; Rao Tian Yu; Jia Qian; Song Jin Zhong; Yi Ben Shun

来源：Journal of Optoelectronics - Laser, 2014, 25(7): 1415-1424.

• Image fusion algorithms
• Information entropy
• Laplacian Pyramid
• Overall visual qualities
• Reconstruction error
• Standard deviation
• Subjective quality
• Transition regions

Due to the classical Laplacian pyramid image fusion algorithms are in loss of image details and moving objects resulting in fusion ghosting in image stiching, an image fusion algorithm of Laplacian pyramid based on graph cuting is proposed in this paper. Firstly, an optimal seam is found via graph cuting introduced. Then an adaptive transition region is proposed to remove the fusion ghosting. Secondly, the reconstruction error is compensated by the details of the original image. The weighted fusion algorithm is proposed with consideration of multi-direction, including horizontal direction. The source images and the fused images of Laplacian pyramid are merged together according to the fusion rules. Compared with classical Laplacian fusion method, experimental results show that the method proposed in this paper performs best in terms of subjective quality and objective indicators. Objectively, it improves image average by an average of 0.326, standard deviation by an average of 1.109, information entropy by an average of 0.041 and image definition by an average of 0.289. Subjectively, it retains the image details and then improves the quality of fusion without obvious stitching artifacts and fusion ghosting. The panorama stitching is more true and the overall visual quality is improved.

• 出版日期2014
• 单位测绘遥感信息工程国家重点实验室