Abstract
An intrinsic co-decomposition model is presented for stereoscopic images. To build the correlation of inter-image or intra-image, the sparse subspace clustering in superpixel level and K-mean clustering in pixel level are implemented. With the constraints on correlation, stereoscopic images are decomposed simultaneously and the reflectance components with more details and higher contrasts are obtained for the edge-preserving of superpixel and the local reflectance correlation of pixels. Experiments show that the reflectance components of co-decomposition are clearer visually. Furthermore, information entropy and standard deviation of reflectance components of co-decomposition are calculated to validate the effectiveness quantitatively of the co-decomposition.
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Acknowledgment
This work has been partially supported by the National Natural Science Foundation of China under grant Nos. 6150238, 61501370, 61703333.
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Li, X., Jin, H., Xiao, Z., Shi, L. (2019). Intrinsic Co-decomposition for Stereoscopic Images. In: El Rhalibi, A., Pan, Z., Jin, H., Ding, D., Navarro-Newball, A., Wang, Y. (eds) E-Learning and Games. Edutainment 2018. Lecture Notes in Computer Science(), vol 11462. Springer, Cham. https://doi.org/10.1007/978-3-030-23712-7_20
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DOI: https://doi.org/10.1007/978-3-030-23712-7_20
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