Abstract
Multi-focus image fusion scheme integrates multiple input images to obtain a composite fused image. Many research works have been carried out since years and various image fusion approaches were developed. The main idea behind the image fusion is to generate a fused image with enhanced quality and containing more information than that of individual source images. Nowadays, these image fusion techniques are implemented in many applications to combine multi-focus image data into a single composite image. Image fusion models can be categorized into two ways, spatial based fusion and transform based fusion. Transform based fusion is performed in three steps, (1) In the first step, transform coefficients from the input images are turned into transform domain frequencies. (2) In the second step, by applying the fusion rule, these transform coefficients are combined. (3) Through the process of inverse transform on the combined correlated images, fused composite image is generated. In this paper, we have introduced a novel region segmentation based multi-focus image fusion model and implemented it. Proposed model was thoroughly studied, analyzed, and compared with different multi-focus fusion models. Experimental results prove that the proposed model has high computational accuracy in terms of image quality and less error rate compared to traditional models.
References
Kim, Hyung-Tae et al. “Optical Distance Control for A Multi Focus Image In Camera Phone Module Assembly”. International Journal of Precision Engineering and Manufacturing 12.5 (2011): 805–811. Web. 19 Mar. 2017.
Lee, Seung-Hyun et al. “Multi-Focus Image Fusion By Using A Pixel-Based SML Comparison Map”. Computer Science and its Applications (2015): 615–621. Web. 19 Mar. 2017.
Shreyamsha Kumar, B. K. “Multifocus And Multispectral Image Fusion Based On Pixel Significance Using Discrete Cosine Harmonic Wavelet Transform”. Signal, Image and Video Processing 7.6 (2012): 1125–1143. Web. 19 Mar. 2017.
T. Zaveri, M. Zaveri, V. Shah and N. Patel, “A Novel Region Based Multi-focus Image Fusion Method”, “Journal of Digital Image Processing”, pp. 50–54, 2009.
Xuejun, Li, and Wang Minghui. “Research Of Multi-Focus Image Fusion Algorithm Based On Sparse Representation And Orthogonal Matching Pursuit”. Communications in Computer and Information Science (2014): 57–66. Web. 19 Mar. 2017.
L. Xu, J. Du, J. M. Lee, Q. Hu, Z. Zhang, M. Fang and Q. Wang, “Multi-focus Image Fusion Using Local Perceived Sharpness”, “25th Chinese Control and Decision Conference (CCDC)”, pp. 3223–3227, 2013.
“Multifocus Image Fusion Based On NSCT and Focused Area Detection - IEEE Xplore Document”. Ieeexplore.ieee.org. N.p., 2017. Web. 19 Mar. 2017.
T. Wan, Z. Qin, C. Zhu and R. Liao, “A Robust Scheme for Multi-focus Images using Sparse Features”, “Pattern Recognition Letters 34.9”, pp. 1957–1961, 2013.
Zhong, Fuping, Yaqi Ma, and Huafeng Li. “Multifocus Image Fusion Using Focus Measure Of Fractional Differential And NSCT”. Pattern Recognition and Image Analysis 24.2 (2014): 234–242. Web. 19 Mar. 2017.
Yong Yang, “A Novel DWT Based Multi-Focus Image Fusion Method – Science direct”.
N. Ma, L. Luo, Z. Zhou and M. Liang, “A multifocus image fusion in non sub sampled contourlet domain with variational fusion strategy”, “Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR 2011)”, 2011.
H. Li, Y. Chai and Z. Li, “A new fusion scheme for multifocus images based on focused pixels detection”, “Machine vision and applications 24.6”, pp. 1167–1181, 2013.
H. Hariharan, A. Koschan and M. Abidi, “Multi-focus Image Fusion By establishing Focal Connectivity”, “IEEE International Conference on Image Processing. Vol. 3”, 2007.
S. Gabarda and G. Cristo´ bal, “Multifocus image fusion n through pseudo-Wigner Distribution”, “Optical Engineering-44.4”, 2005.
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Ravikanth, G., Sunitha, K.V.N., Eswara Reddy, B. (2018). A Novel Region Segmentation-Based Multi-focus Image Fusion Model. In: Chaki, N., Cortesi, A., Devarakonda, N. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 9. Springer, Singapore. https://doi.org/10.1007/978-981-10-6319-0_21
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DOI: https://doi.org/10.1007/978-981-10-6319-0_21
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