Abstract
We present a new colorization method to assign color to a grayscale image based on a reference color image using texture descriptors and Improved Simple Linear Iterative Clustering (ISLIC). Firstly, the pixels of images are classified using Support Vector Machine (SVM) according to texture descriptors, mean luminance, entropy, homogeneity, correlation, and local binary pattern (LBP) features. Then, the grayscale image and the color image are segmented into superpixels, which are obtained by ISLIC to produce more uniform and regularly shaped superpixels than those obtained by SLIC, and the classified images are further post-processed combined with superpixles for removing erroneous classifications. Thereafter, each pixel of the grayscale image is assigned with a color obtained from the color image following a predefined matching metric based on the superpixels and the classes. Experimental results show that our proposed approach is effective and has a better colorization in naturalness compared with Welsh algorithm and unimproved SLIC strategy method.
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References
Bugeau, A., Ta, V. T., Papadakis, N. (2014): Variational exemplar-based image colorization. IEEE Transactions on Image Processing, 23(1), 298–307
Welsh, T., Ashikhmin, M., Mueller, K. (2002): Transferring color to greyscale images. ACM Transactions on Graphics (TOG), 21(3), 277–280
Irony, R., Cohen-Or, D., Lischinski, D. (2005): Colorization by example. In: Proceedings of the 16th Eurographics Conference on Rendering Techniques, pp. 201–210. Eurographics Association Aire-la-Ville Press, Switzerland
Charpiat, G., Hofmann, M., Schölkopf, B. (2008): Automatic image colorization via multi-modal predictions. In: 10th European Conference on Computer Vision, pp. 126–139. Springer Berlin Heidelberg Marseille, Marseille, France
Gupta, R.K., Chia, A.Y.S., Rajan, D., Ng, E.S., Huang, Z.Y. (2012): Image colorization using similar images. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 369–378. ACM New York Press, Nara, Japan
Ojala, T., Pietikäinen, M. Mäenpää, T. (2002): Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), 971–987
Achanta, R., Shaji, A., Smith, K., Lucchi, A., Süsstrunk, S. (2012): Slic superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11), 2274–2281
Kim, K.S., Zhang, D., Kang, M.C., Ko. S.J. (2013): Improved simple linear iterative clustering superpixels. In: IEEE International Symposium on Consumer Electron, pp. 259–260. Hsinchu, Taiwan
Jain, V., Learned-Miller,E. (2010): Fddb: A benchmark for face detection in unconstrained settings. Technical Report UMCS-2010–009. University of Massachusetts, Amherst
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This study is funded by National Natural Science Foundation of China (41201449).
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Cao, L., Jiao, L., Li, Z. (2017). Image Colorization Method Using Texture Descriptors and ISLIC Segmentation. In: Zhao, P., Ouyang, Y., Xu, M., Yang, L., Ouyang, Y. (eds) Advanced Graphic Communications and Media Technologies . PPMT 2016. Lecture Notes in Electrical Engineering, vol 417. Springer, Singapore. https://doi.org/10.1007/978-981-10-3530-2_2
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DOI: https://doi.org/10.1007/978-981-10-3530-2_2
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