- -

Fusión de Imágenes Multi-Foco con Ventanas Variables

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Fusión de Imágenes Multi-Foco con Ventanas Variables

Show full item record

Calderon, F.; Garnica-Carrillo, A.; Flores, JJ. (2018). Fusión de Imágenes Multi-Foco con Ventanas Variables. Revista Iberoamericana de Automática e Informática industrial. 15(3):262-276. https://doi.org/10.4995/riai.2017.8852

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/143095

Files in this item

Item Metadata

Title: Fusión de Imágenes Multi-Foco con Ventanas Variables
Secondary Title: Multi Focus Image Fusion with variable size windows
Author: Calderon, Felix Garnica-Carrillo, Adan Flores, Juan J.
Issued date:
Abstract:
[EN] In this paper we present the Linear Image Combination Algorithm with Variable Windows (CLI-VV) for the fusion of multifocus images. Unlike the CLI-S algorithm presented in a previous work, the CLI-VV algorithm allows ...[+]


[ES] En este artículo presentamos el Algoritmo Combinación Lineal de Imágenes con Ventanas Variables (CLI-VV) para la fusión de imágenes multi-foco. A diferencia del Algoritmo CLI-S presentado en un trabajo anterior, el ...[+]
Subjects: Multi-focus image fusion , Sliding windows , Incremental images , Fusión de imágenes multi-foco , Ventanas deslizantes , Imágenes integrales
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Revista Iberoamericana de Automática e Informática industrial. (issn: 1697-7912 ) (eissn: 1697-7920 )
DOI: 10.4995/riai.2017.8852
Publisher:
Universitat Politècnica de València
Publisher version: https://doi.org/10.4995/riai.2017.8852
Type: Artículo

References

Aslantas, V., Kurban, R., 2010. Fusion of multi-focus images using differential evolution algorithm. Expert Systems with Applications 37 (12), 8861 - 8870. https://doi.org/10.1016/j.eswa.2010.06.011

Aslantas, V., Toprak, A. N., 2014. A pixel based multi-focus image fusion method. Optics Communications 332, 350 - 358. https://doi.org/10.1016/j.optcom.2014.07.044

Aslantas, V., Toprak, A. N., 2017. Multi-focus image fusion based on optimal defocus estimation. Computers and Electrical Engineering. https://doi.org/10.1016/j.compeleceng.2017.02.003 [+]
Aslantas, V., Kurban, R., 2010. Fusion of multi-focus images using differential evolution algorithm. Expert Systems with Applications 37 (12), 8861 - 8870. https://doi.org/10.1016/j.eswa.2010.06.011

Aslantas, V., Toprak, A. N., 2014. A pixel based multi-focus image fusion method. Optics Communications 332, 350 - 358. https://doi.org/10.1016/j.optcom.2014.07.044

Aslantas, V., Toprak, A. N., 2017. Multi-focus image fusion based on optimal defocus estimation. Computers and Electrical Engineering. https://doi.org/10.1016/j.compeleceng.2017.02.003

Assirati, L., Silva, N. R., Berton, L., Lopes, A. A., Bruno, O. M., 2014. Performing edge detection by difference of gaussians using q-gaussian kernels. Journal of Physics: Conference Series 490 (1), 012020. https://doi.org/10.1088/1742-6596/490/1/012020

Bai, X., Zhang, Y., Zhou, F., Xue, B., 2015. Quadtree-based multi-focus image fusion using a weighted focus-measure. Information Fusion 22, 105 - 118. https://doi.org/10.1016/j.inffus.2014.05.003

Calderon, F., Garnica, A., 2014. Multi focus image fusion based on linear combination of images. IEEE, pp. 1-7. https://doi.org/10.1109/ROPEC.2014.7036340

Calderon, F., Garnica-Carrillo, A., Flores, J. J., 2016. Fusión de imágenes multi foco basado en la combinación lineal de imágenes utilizando imágenes incrementales. Revista Iberoamericana de Automática e Informática Industrial RIAI 13 (4), 450 - 461. https://doi.org/10.1016/j.riai.2016.07.002

Cao, L., Jin, L., Tao, H., Li, G., Zhuang, Z., Zhang, Y., Feb 2015. Multi-focus image fusion based on spatial frequency in discrete cosine transform domain. Signal Processing Letters, IEEE 22 (2), 220-224. https://doi.org/10.1109/LSP.2014.2354534

Chai, Y., Li, H., Li, Z., 2011. Multifocus image fusion scheme using focused region detection and multiresolution. Optics Communications 284 (19), 4376 - 4389. https://doi.org/10.1016/j.optcom.2011.05.046

De, I., Chanda, B., 2013. Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure. Information Fusion 14 (2), 136 - 146. https://doi.org/10.1016/j.inffus.2012.01.007

Duan, J., Meng, G., Xiang, S., Pan, C., 2014. Multifocus image fusion via focus segmentation and region reconstruction. Neurocomputing 140, 193 - 209. https://doi.org/10.1016/j.neucom.2014.03.023

Eskicioglu, A., Fisher, P., Dec 1995. Image quality measures and their performance. Communications, IEEE Transactions on 43 (12), 2959-2965. https://doi.org/10.1109/26.477498

Kong, W., Lei, Y., 2017. Multi-focus image fusion using biochemical ion exchange model. Applied Soft Computing 51, 314 - 327. https://doi.org/10.1016/j.asoc.2016.11.033

Kuthirummal, S., Nagahara, H., Zhou, C., Nayar, S., Jan 2011. Flexible depth of field photography. Pattern Analysis and Machine Intelligence, IEEE Transactions on 33 (1), 58-71. https://doi.org/10.1109/TPAMI.2010.66

Lewis, J. J., O'Callaghan, R. J., Nikolov, S. G., Bull, D. R., Canagarajah, N., 2007. Pixel- and region-based image fusion with complex wavelets. Information Fusion 8 (2), 119 - 130, special Issue on Image Fusion: Advances in the State of the Art. https://doi.org/10.1016/j.inffus.2005.09.006

Li, H., Chai, Y., Li, Z., 2013a. Multi-focus image fusion based on nonsubsampled contourlet transform and focused regions detection. Optik - International Journal for Light and Electron Optics 124 (1), 40 - 51. https://doi.org/10.1016/j.ijleo.2011.11.088

Li, H., Chai, Y., Li, Z., 2013b. A new fusion scheme for multifocus images based on focused pixels detection. Machine vision and applications 24 (6), 1167-1181. https://doi.org/10.1007/s00138-013-0502-4

Li, H., Manjunath, B., Mitra, S., 1995. Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing 57 (3), 235 - 245. https://doi.org/10.1006/gmip.1995.1022

Li, S., Kang, X., Fang, L., Hu, J., Yin, H., 2017. Pixel-level image fusion: A survey of the state of the art. Information Fusion 33, 100 - 112. https://doi.org/10.1016/j.inffus.2016.05.004

Li, S., Kwok, J. T., Wang, Y., 2001. Combination of images with diverse focuses using the spatial frequency. Information Fusion 2 (3), 169 - 176. https://doi.org/10.1016/S1566-2535(01)00038-0

Li, S., Kwok, J. T., Wang, Y., 2002. Multifocus image fusion using artificial neural networks. Pattern Recognition Letters 23 (8), 985 - 997. https://doi.org/10.1016/S0167-8655(02)00029-6

Li, S., Yang, B., 2008a. Multifocus image fusion by combining curvelet and wavelet transform. Pattern Recognition Letters 29 (9), 1295-1301. https://doi.org/10.1016/j.patrec.2008.02.002

Li, S., Yang, B., 2008b. Multifocus image fusion using region segmentation and spatial frequency. Image and Vision Computing 26 (7), 971 - 979. https://doi.org/10.1016/j.imavis.2007.10.012

Li, X., He, M., Roux, M., August 2010. Multifocus image fusion based on redundant wavelet transform. Image Processing, IET 4 (4), 283-293. https://doi.org/10.1049/iet-ipr.2008.0259

Liu, Y., Chen, X., Peng, H., Wang, Z., 2017a. Multi-focus image fusion with a deep convolutional neural network. Information Fusion 36, 191 - 207. https://doi.org/10.1016/j.inffus.2016.12.001

Liu, Z., Chai, Y., Yin, H., Zhou, J., Zhu, Z., 2017b. A novel multi-focus image fusion approach based on image decomposition. Information Fusion 35, 102 - 116. https://doi.org/10.1016/j.inffus.2016.09.007

Long, J., Shelhamer, E., Darrell, T., 2014. Fully convolutional networks for semantic segmentation. CoRR abs/1411.4038.

Luo, X., Zhang, J., Dai, Q., 2012. A regional image fusion based on similarity characteristics. Signal Processing 92 (5), 1268 - 1280. https://doi.org/10.1016/j.sigpro.2011.11.021

Ma, Y., Zhan, K.,Wang, Z., service), S. O., 2011. Applications of pulse-coupled neural networks.

Malviya, A., Bhirud, S., Dec 2009. Wavelet based multi-focus image fusion. In: Methods and Models in Computer Science, 2009. ICM2CS 2009. Proceeding of International Conference on. pp. 1-6. https://doi.org/10.1109/ICM2CS.2009.5397990

Nejati, M., Samavi, S., Shirani, S., 2015. Multi-focus image fusion using dictionary-based sparse representation. Information Fusion 25, 72 - 84. https://doi.org/10.1016/j.inffus.2014.10.004

Orozco, R. I., 2013. Fusión de imágenes multifoco por medio de filtrado de regiones de alta y baja frecuencia. Master's thesis, División de Estudios de Postgrado. Facultad de Ingeniería Eléctrica. UMSNH, Morelia Michoacan Mexico.

Pagidimarry, M., Babu, K. A., 2011. An all approach for multi-focus image fusion using neural network. Artificial Intelligent Systems and Machine Learning 3 (12), 732-739.

Pajares, G., de la Cruz, J. M., 2004. A wavelet-based image fusion tutorial. Pattern Recognition 37 (9), 1855 - 1872. https://doi.org/10.1016/j.patcog.2004.03.010

Piella, G., 2003. A general framework for multiresolution image fusion: from pixels to regions. Information Fusion 4 (4), 259 - 280. https://doi.org/10.1016/S1566-2535(03)00046-0

Pramanik, S., Prusty, S., Bhattacharjee, D., Bhunre, P. K., 2013. A region-topixel based multi-sensor image fusion. Procedia Technology 10, 654 - 662. https://doi.org/10.1016/j.protcy.2013.12.407

Qu, X., Hou, Y., Lam, F., Guo, D., Zhong, J., Chen, Z., 2014. Magnetic resonance image reconstruction from undersampled measurements using a patchbased nonlocal operator. Medical Image Analysis 18 (6), 843 - 856, sparse Methods for Signal Reconstruction and Medical Image Analysis. https://doi.org/10.1016/j.media.2013.09.007

Riaz, M., Park, S., Ahmad, M., Rasheed, W., Park, J., 2008. Generalized laplacian as focus measure. In: Bubak, M., van Albada, G., Dongarra, J., Sloot, P. (Eds.), Computational Science ICCS 2008. Vol. 5101 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 1013-1021. https://doi.org/10.1007/978-3-540-69384-0_106

Rivera, M., Ocegueda, O., Marroquin, J., Dec 2007. Entropy-controlled quadratic markov measure field models for efficient image segmentation. Image Processing, IEEE Transactions on 16 (12), 3047-3057. https://doi.org/10.1109/TIP.2007.909384

Sezan, M., Pavlovic, G., Tekalp, A., Erdem, A., Apr 1991. On modeling the focus blur in image restoration. In: Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on. pp. 2485-2488 vol.4. https://doi.org/10.1109/ICASSP.1991.150905

Shah, P., Merchant, S. N., Desai, U. B., 2013. Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition. Signal, Image and Video Processing 7 (1), 95-109. https://doi.org/10.1007/s11760-011-0219-7

Shi, W., Zhu, C., Tian, Y., Nichol, J., 2005. Wavelet-based image fusion and quality assessment. International Journal of Applied Earth Observation and Geoinformation 6 (3-4), 241 - 251. https://doi.org/10.1016/j.jag.2004.10.010

Tian, J., Chen, L., Sept 2010. Multi-focus image fusion using wavelet-domain statistics. In: Image Processing (ICIP), 2010 17th IEEE International Conference on. pp. 1205-1208. https://doi.org/10.1109/ICIP.2010.5651791

Viola, P., Jones, M., 2001. Rapid object detection using a boosted cascade of simple features. In: Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. Vol. 1. pp. I-511-I-518 vol.1. https://doi.org/10.1109/CVPR.2001.990517

Yang, Y., 2011. A novel fDWTg based multi-focus image fusion method. Procedia Engineering 24 (0), 177 - 181, international Conference on Advances in Engineering 2011.

Yang, Y., Huang, S., Gao, J., Qian, Z., 2014. Multi-focus image fusion using an effective discrete wavelet transform based algorithm. Measurement Science Review 14 (2), 102 - 108. https://doi.org/10.2478/msr-2014-0014

Yang, Y., Tong, S., Huang, S., Lin, P., 2015. Multifocus image fusion based on nsct and focused area detection. IEEE Sensors Journal 15 (5), 2824-2838. Zhang, B., Lu, X., Pei, H., Liu, H., Zhao, Y., Zhou, W., 2016a. Multi-focus image fusion algorithm based on focused region extraction. Neurocomputing 174, 733 - 748. https://doi.org/10.1016/j.neucom.2015.09.092

Zhang, Q., long Guo, B., 2009. Multifocus image fusion using the nonsubsampled contourlet transform. Signal Processing 89 (7), 1334 - 1346. https://doi.org/10.1016/j.sigpro.2009.01.012

Zhang, Y., Chen, L., Zhao, Z., Jia, J., 2016b. Multi-focus image fusion based on cartoon-texture image decomposition. Optik - International Journal for Light and Electron Optics 127 (3), 1291 - 1296. https://doi.org/10.1016/j.ijleo.2015.10.098

Zhang, Z., Blum, R., Aug 1999. A categorization of multiscale-decompositionbased image fusion schemes with a performance study for a digital camera application. Proceedings of the IEEE 87 (8), 1315-1326. https://doi.org/10.1109/5.775414

Zhao, H., Li, Q., Feng, H., 2008. Multi-focus color image fusion in the HSI space using the sum-modified-laplacian and a coarse edge map. Image and Vision Computing 26 (9), 1285 - 1295. https://doi.org/10.1016/j.imavis.2008.03.007

Zhou, L., Ji, G., Shi, C., Feng, C., Nian, R., 2006. A Multi-focus Image Fusion Method Based on Image Information Features and the Artificial Neural Networks. Vol. 344. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 747-752. https://doi.org/10.1007/978-3-540-37256-1_91

Zhou, Z., Li, S., Wang, B., 2014. Multi-scale weighted gradient-based fusion for multi-focus images. Information Fusion 20 (0), 60 - 72. https://doi.org/10.1016/j.inffus.2013.11.005

[-]

This item appears in the following Collection(s)

Show full item record