Abstract
In this chapter, we describe two upscaling methods for photo printers. They are both based on constructing an edge map and interpolating known image values along the edges, preserving the edge structure, and avoiding the appearance of artefacts. The interpolation process is followed by a post-processing stage, where edges are emphasized using a specially designed tone-mapping curve. The second algorithm uses structure tensor analysis to distinguish edges from textured areas and to find local structure direction vectors. The vectors are quantized into six directions. Individual adaptive interpolation kernels are used for each direction. The new methods provide high-resolution images with sharper edges, with quality higher than that obtained by bilinear interpolation, and require less computation than higher order bi-cubic methods.
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References
Allebach, J., Wong, P.: Edge-directed interpolation. In: Proceedings of International Conference on Image Processing, vol. 3, pp. 707–710 (1996)
Belekos, S., Galatsanos, N., Katsaggelos, A.: Maximum a posteriori video super-resolution using a new multichannel image prior. IEEE Trans. Image Process. 19(6), 1451–1464 (2010)
Blu, T., Thvenaz, T., Unser, M.: Generalized interpolation: higher quality at no additional cost. In: Proceedings of International Conference on Image Processing, vol. III, pp. 667–671 (1999)
Chan, T., Shen, J.: Image Processing And Analysis: Variational, PDE, Wavelet, And Stochastic Methods. Society for Industrial and Applied Mathematics (2005)
Dai, D., Timofte, R., Gool, L.V.: Jointly optimized regressors for image super-resolution. Eurographics 34 (2015)
Dong, C., Loy, C.C., He, K., Tang, X.: September. Learning a deep convolutional network for image super-resolution. In: European Conference on Computer Vision, pp. 184–199. Springer International Publishing (2014)
Farsiu, S., Robinson, M., Elad, M., Milanfar, P.: Fast and robust multiframe super resolution. IEEE Trans. Image Process. 13(10), 1327–1344 (2004)
Freedman, G., Fattal, R.: Image and video upscaling from local self-examples. ACM Trans. Graph. (TOG) 30(2), 12 (2011)
Giachetti, A., Asuni, N.: Real-time artefact-free image upscaling. IEEE Trans. Image Process. 20(10), 2760–2768 (2011)
Jensen, K., Anastassiou, D.: Spatial resolution enhancement of images using nonlinear interpolation. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP-90, vol. 4, pp. 2045–2048 (1990)
Kimmel, R.: Demosaicing: image reconstruction from color CCD samples. IEEE Trans. Image Process. 8(9), 1221–1228 (1999)
Li, X., Orchard, M.: New edge directed interpolation. In: IEEE International Conference on Image Processing (2000)
Liu, Z.: Adaptive regularized image interpolation using a probabilistic gradient measure. Opt. Commun. 285(3), 245–248 (2012)
Muresan, D., Parks, T.W.: New image interpolation techniques. IEEE 2000 Western New York Image Processing Workshop (2000)
Peleg, T., Elad, M.: A statistical prediction model based on sparse representations for single image super resolution. IEEE Trans. Image Process. 23(6), 2569–2582 (2014)
Quak, E., Schumaker, L.: Cubic spline interpolation using data dependent triangulations. Comput. Aided Geom. Design 7, 293–301 (1990)
Schulter, S., Leistner, C., Bischof, H. Fast and accurate image upscaling with super-resolution forests, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3791–3799 (2015)
Sheikh, H., Sabir, M., Bovik, A.: A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. Image Process. 15(11), 3440–3451 (2006)
Su, D., Willis, P.: Image Interpolation by Pixel‐Level Data‐Dependent Triangulation. In: Computer Graphics Forum, vol. 23(2), pp. 189–201. Blackwell Publishing Ltd. (2004)
Thévenaz, P., Blu, T., Unser, M.: Interpolation revisited. IEEE Trans. Med. Imaging 19(7), 739–758 (2000)
Yu, X., Morse, B., Sederberg, T.: Image reconstruction using data-dependent triangulation. IEEE Comput. Graphics Appl. 21(3), 62–68 (2001)
Yu, S., Zhu, Q., Wu, S., Xie, Y.: Performance evaluation of edge-directed interpolation methods for images. Comput. Vis. Pattern Recognit. (2013)
Zhou, D., Shen, X., Dong, W.: Image zooming using directional cubic convolution interpolation. IET Image Proc. 6(6), 627–634 (2012)
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Safonov, V.I., Kurilin, V.I., Rychagov, N.M., Tolstaya, V.E. (2018). Image Upscaling. In: Adaptive Image Processing Algorithms for Printing. Signals and Communication Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-6931-4_8
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DOI: https://doi.org/10.1007/978-981-10-6931-4_8
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