Abstract
Fusion of multifocus images in discrete cosine transform (DCT) domain has been extensively exploited in recent years due to low complexity. In particular, the fusion by DCT is useful in visual sensor networks (VSN), where the images have to be transferred in coded format. Many research works have been done by combining spatial domain methods in DCT domain. In the proposed work, the energy of correlation coefficient in DCT domain is chosen as fusion criteria. The method works by evaluating the focus measurement between the input images and Laplacian-based sharpened images in DCT domain. The results obtained by the proposed method are compared in terms of objective metrics and the results show that the proposed work avoids inappropriate block selection which exists in available methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Oral, M., Sevgi Turgut, S.: A comparative study for image fusion. In: Innovations in Intelligent Systems and Applications Conference (ASYU), pp. 1–6. IEEE (2018)
Tong, Y., Chen, J.: Multi-focus image fusion algorithm in sensor networks. IEEE Access 6, 46794–46800 (2018)
Paramanandham, N., Rajendiran, K., Narayanan, D., Anand, M.: An efficient multi transform based fusion for multi focus images. In: International Conference on Communications and Signal Processing (ICCSP), pp. 0984–0988. IEEE (2015)
Albuquerque, H.R., Ren, T.I., Cavalcanti, G.D.: Image fusion combining frequency domain techniques based on focus. In: 24th International Conference on Tools with Artificial Intelligence, vol. 1, pp. 757–762. IEEE (2012)
Amin-Naji, M., Aghagolzadeh, A., Ezoji, M.: Ensemble of CNN for multi-focus image fusion. Information Fusion (2019)
Amin-Naji, M., Ranjbar-Noiey, P., Aghagolzadeh, A.: Multi-focus image fusion using singular Value decomposition in DCT domain. In: 10th Iranian Conference on Machine Vision and Image Processing (MVIP), pp. 45–51. IEEE (2017)
Abdollahzadeh, M., Malekzadeh, T., Seyedarabi, H.: Multi-focus image fusion for visual sensor networks. In: 24th Iranian Conference on Electrical Engineering (ICEE), pp. 1673–1677. IEEE (2016)
Kalaivani, K., Phamila, Y.A.V.: Analysis of image fusion techniques based on quality assessment metrics. Indian J. Sci. Technol. 9(31), 1–8 (2016)
Jagalingam, P., Hegde, A.V.: A review of quality metrics for fused image. Aquatic Procedia 4, 133–142 (2015)
Amin-Naji, M., Aghagolzadeh, A., Ezoji, M.: CNNs hard voting for multi-focus image fusion. J. Ambient Intell. Humanized Comput., 1–21 (2019)
Mahapatra, S., Sa, K.D., Dash, D.: DCT Based Multifocus image fusion for wireless sensor networks. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 871–875. IEEE (2018)
Zhang, Y., Wei, W., Yuan, Y.: Multi-focus image fusion with alternating guided filtering. Sig. Image Video Process., 1–9 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sreeja, G., Saraniya, O. (2021). Energy Efficient Multifocus Image Fusion in DCT Domain. In: Suresh, P., Saravanakumar, U., Hussein Al Salameh, M. (eds) Advances in Smart System Technologies. Advances in Intelligent Systems and Computing, vol 1163. Springer, Singapore. https://doi.org/10.1007/978-981-15-5029-4_59
Download citation
DOI: https://doi.org/10.1007/978-981-15-5029-4_59
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5028-7
Online ISBN: 978-981-15-5029-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)