Abstract
Image stitching has developed rapidly in recent years. Seam elimination plays a critical role in image stitching. Therefore, an improved seam elimination method of image stitching is proposed in the paper. First of all, images are registered. Then, optimal seam method based on Curvelet transformation is proposed to eliminate the seam. Objective evaluation indexes (PSNR and SSIM) are employed to evaluate the performance of the proposed method in the experimental results. A new metric of assessing the local quality of the stitched image is also proposed in the paper. Three groups of images are tested under this metric. Experimental results show that our method can eliminate the seam in an efficient way.
















Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Candes E, Demanet L (2003) Curvelets and Fourier integral operators. CR Math 336(5):395–398
Candes EJ, Guo F (2002) New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction. Sig Process 82(11):1519–1543
Chen M, Nian R, He B, et al. (2015) Underwater image stitching based on SIFT and wavelet fusion. In: Proceedings of the OCEANS 2015-Genova, F, IEEE
Eden A, Uyttendaele M, Szeliski R (2006) Seamless image stitching of scenes with large motions and exposure differences. In: Proceedings of the computer vision and pattern recognition, 2006 IEEE Computer Society Conference on, F, IEEE
Fischler MA, Bolles RC (1981) Random sample consensus—a paradigm for model-fitting with applications to image-analysis and automated cartography. Commun ACM 24(6):381–395
Guo-ting W, Jun-ping W, Jin L et al (2013) Method for quality assessment of image mosaic. J Commun 8:011
Hou WL, Gao XB, Tao DC et al (2015) Blind image quality assessment via deep learning. IEEE Trans Neural Netw Learn Syst 26(6):1275–1286
Hui FM, Cheng X, Liu Y et al (2013) An improved Landsat Image Mosaic of Antarctica. Sci China-Earth Sci 56(1):1–12
Huynh-Thu Q, Ghanbari M (2008) Scope of validity of PSNR in image/video quality assessment. Electron Lett 44(13):800–U835
Jia J, Tang C-K (2005) Eliminating structure and intensity misalignment in image stitching. In: proceedings of the Computer Vision, 2005, Tenth IEEE International Conference onICCV 2005, F
Jia JY, Tang CK (2008) Image stitching using structure deformation. IEEE Trans Pattern Anal Mach Intell 30(4):617–631
Kekec T, Yildirim A, Unel M (2014) A new approach to real-time mosaicing of aerial images. Robot Auton Syst 62(12):1755–1767
Lee D, Lee S (2017) Seamless image stitching by homography refinement and structure deformation using optimal seam pair detection. J Electron Imaging 26(6):063016
Li H, Manjunath BS, Mitra SK (1995) Multisensor image fusion using the wavelet transform. Graph Models Image Process 57(3):235–245
Li HY, Luo J, Huang CJ et al (2014) An Adaptive Image-stitching Algorithm for an Underwater Monitoring System. Int J Adv Robot Syst 11:166
Ma X, Liu D, Zhang J et al (2015) A fast affine-invariant features for image stitching under large viewpoint changes. Neurocomputing 151:1430–1438
Miao QG, Shi C, Xu PF et al (2011) A novel algorithm of image fusion using shearlets. Opt Commun 284(6):1540–1547
Mills A, Dudek G (2009) Image stitching with dynamic elements. Image Vis Comput 27(10):1593–1602
Ponomarenko N, Lukin V, Zelensky A et al (2009) TID2008-a database for evaluation of full-reference visual quality assessment metrics. Adv Mod Radioelectr 10(4):30–45
Sadeghi MA, Hejrati SMM, Gheissari N (2008) Poisson local color correction for image stitching. In: Proceedings of the VISAPP (1), F,
Shi WZ, Zhu CQ, Tian Y et al (2005) Wavelet-based image fusion and quality assessment. Int J Appl Earth Obs Geoinf 6(3–4):241–251
Shulong Z, Zengbo Q (2002) The seam-line removal under mosaicking of remotely sensed images. J Remote Sens 6(3):183–187
Starck JL, Candes EJ, Donoho DL (2002) The curvelet transform for image denoising. IEEE Trans Image Process 11(6):670–684
Starck JL, Murtagh F, Candes EJ et al (2003) Gray and color image contrast enhancement by the curvelet transform. IEEE Trans Image Process 12(6):706–717
Tian JY, Li XJ, Duan FZ et al (2016) An efficient seam elimination method for UAV images based on wallis dodging and gaussian distance weight enhancement. Sensors 16(5):662
Wang Z, Bovik AC (2002) A universal image quality index. IEEE Signal Process Lett 9(3):81–84
Wang L, Chu J (2011) Fused multi-sensor information image stitching. In: Proceedings of the international conference on intelligent science and intelligent data engineering, F. Springer
Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612
Wang ZB, Ma YD, Gu J (2010) Multi-focus image fusion using PCNN. Pattern Recogn 43(6):2003–2016
Xie X, Xu Y, Liu Q et al (2015) A study on fast SIFT image mosaic algorithm based on compressed sensing and wavelet transform. J Ambient Intell Humaniz Comput 6(6):835–843
Xu Y, Sun C (2017) Image stitching method based on genetic algorithm [M]//Hou H, Han Z. Proceedings of the 2017 5th international conference on machinery, materials and computing technology. pp 406–412
Yang F, Deng ZS, Fan QH (2013) A method for fast automated microscope image stitching. Micron 48:17–25
Ye MJ, Li J, Liang YY et al (2011) Automatic seamless stitching method for CCD images of Chang’E-1 lunar mission. J Earth Sci 22(5):610–618
Yue Z, Hong C, Wen-bang S (2014) Finding an optimal seam-line through the shortest distance in the neighborhood. Chin J Image Graph 19(2):227–233
Zaragoza J, Chin T-J, Brown MS, et al (2013) As-projective-as-possible image stitching with moving DLT. In: proceedings of the computer vision and pattern recognition (CVPR), 2013 IEEE Conference on, F. IEEE
Zhang Q, Guo BL (2009) Multifocus image fusion using the nonsubsampled contourlet transform. Sig Process 89(7):1334–1346
Zhang J, Chen G, Jia Z (2017) An image stitching algorithm based on histogram matching and SIFT algorithm. Int J Pattern Recognit Artif Intell 31(04):1754006
Zomet A, Levin A, Peleg S et al (2006) Seamless image stitching by minimizing false edges. IEEE Trans Image Process 15(4):969–977
Acknowledgements
This work was jointly supported by National Natural Science Foundation of China (Grant No. 61201421) and the Fundamental Research Funds for the Central Universities(lzujbky-2017-187).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflicts of interest
The authors declare that they have no potential conflict of interest.
Additional information
Communicated by V. Loia.
Rights and permissions
About this article
Cite this article
Wang, Z., Yang, Z. Seam elimination based on Curvelet for image stitching. Soft Comput 23, 5065–5080 (2019). https://doi.org/10.1007/s00500-018-3175-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-018-3175-0