基于结构成分双向扩散的图像插值算法

贾茜; 易本顺; 肖进胜

doi:10.3724/SP.J.1146.2014.00255

基于结构成分双向扩散的图像插值算法

doi: 10.3724/SP.J.1146.2014.00255

武汉大学电子信息学院武汉 430072

基金项目:

国家自然科学基金(91120002)资助课题

计量
- 文章访问数: 2546
- HTML全文浏览量: 77
- PDF下载量: 1285
- 被引次数: 0
出版历程
- 收稿日期: 2014-02-26
- 修回日期: 2014-07-03
- 刊出日期: 2014-11-19

Image Interpolation Algorithm Based on Structure Component Bidirectional Diffusion

摘要

摘要: 该文提出一种基于结构成分双向扩散的插值方法，有效地减小了插值图像的边缘扩散，从而获得更为清晰的边缘。该方法采用改进的耦合双向扩散滤波器对轮廓模板插值图像进行边缘增强。其中，为了使滤波器更精确地作用于边缘轮廓，利用形态成分分析(MCA)分离出初始插值图像中的结构分量再实行滤波；同时，改进双向扩散模型，使其能够根据边缘梯度自适应地调整边缘扩散程度，且更加柔和地控制梯度方向的像素值变化。实验结果表明，对比传统的插值方法、相关的边缘自适应插值方法以及几种应用普遍的商用软件，该方法获得的插值图像主、客观质量均有明显提升，不仅有效提高图像锐度，且边缘光滑、过渡自然，避免产生边缘锯齿和过度的人工效应。
- 图像处理 /
- 图像插值 /
- 双向扩散 /
- 形态成分分析 /
- 边缘增强
Abstract: An image interpolation method based on structure component bidirectional diffusion is proposed in this paper, by which the edge diffusion in image magnification is effectively decreased and the sharpening edges are generated. In this method, the edges are enhanced by using the advanced coupling of bidirectional diffusion filter after contour stencils interpolation. In order to deal with the edge contours more precisely, the structure component of initial interpolated image is filtered after separating from the initial interpolated image via Morphological Component Analysis (MCA). Furthermore, the coupling of bidirectional filter is improved to adaptively adjust the edge diffusion degree according to the edge gradient, and to control pixels value change along gradient direction more gently. The experimental results show that, the proposed method outperforms other comparing algorithms including the traditional interpolation algorithm and the related edge adaptive interpolation algorithms and several widely-used commercial software in terms of both objective and visual quality of the interpolation image. The method enhances the image sharpness effectively, and gains smooth edges, nature transition, also avoids producing the edge aliasing and overshoot artifacts.
- Image processing /
- Image interpolation /
- Bidirectional diffusion /
- Morphological Component Analysis (MCA) /
- Edge enhance

HTML全文

参考文献(21)

陈瑶, 孙兴波, 黄祥, 等. 一种消除锯齿的图像放大算法[J]. 四川理工学院学报(自然科学版), 2013, 26(3): 35-37.

Chen Yao, Sun Xing-bo, Huang Xiang, et al.. An Algorithm of anti-aliased image magnification[J]. Journal of Sichuan University of Science & Engineering (Natural Science Edition), 2013, 26(3): 35-37.

陈利平. 自适应 Catmull-Rom 样条图像放大[J]. 计算机辅助设计与图形学学报, 2013, 25(2): 200-207.

Chen Li-ping. Image amplification based on adaptive Cammull-Rom interpolation[J]. Journal of Computer-Aided Design & Computer Graphice, 2013, 25(2): 200-207.

席志红, 海涛, 肖易寒. 基于混合非线性偏微分方程扩散的可逆图像放大[J]. 系统工程与电子技术, 2013, 35(5): 1098-1103.

Xi Z H, Hai T, and Xiao Y H. Reversible image interpolation based on hybrid anisotropic partial differential equation diffusion[J]. Systems Engineering and Electronics, 2013, 35(5): 1098-1103.

Aly H and Dubois E. Image up-sampling using total-variation regularization with a new observation model[J]. IEEE Transactions on Image Processing, 2005, 14(10): 1647-1659.

Babacan S D, Molina R, and Katsaggelos A K. Variational Bayesian super resolution[J]. IEEE Transactions on Image Processing, 2011, 20(4): 984-999.

Hiroyuki T, Farsiu S, and Milanfar P. Kernel regression for image processing and reconstruction[J]. IEEE Transactions on Image Processing, 2007, 16(2): 349-366.

周鑫, 胡访宇, 朱高. 基于核回归的正则化超分辨率重建算法[J]. 电子测量技术, 2012, 35(3): 62-68.

Zhou X, Hu F Y, and Zhu G. Super-resolution reconstruction based on adaptive kernel regression[J]. Electronic Measurement Technology, 2012, 35(3): 62-68.

李家德, 张叶, 贾平. 采用非局部均值的超分辨率重构[J]. 光学精密工程, 2013, 21(6): 1576-1585.

Li Jia-de, Zhang Ye, and Jia Ping. Super-resolution reconstruction using nonlocal means[J]. Optics and Precision Engineering, 2013, 21(6): 1576-1585.

冯象初, 姜东焕, 徐光宝. 基于变分和小波变换的图像放大算法[J]. 计算机学报, 2008, 31(2): 340-345.

Feng X C, Jiang D H, and Xu G B. Combining variation and wavelet transform for image zooming[J]. Chinese Journal of Computers, 2008, 31(2): 340-345.

Lu X, Yuan Y, and Yan P. Image super-resolution via double sparsity regularized manifold learning[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2013, 23(12): 2022-2033.

Yang J C, Wright J, Huang T S, et al.. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 2010, 19(11): 2861-2873.

孙士保, 段建辉. 一种基于边缘梯度的图像插值算法[J]. 计算机工程, 2013, 39(8): 239-242.

Sun Shi-bao and Duan Jian-hui. An image interpolation algorithm based on edge gradient[J]. Computer Engineering, 2013, 39(8): 239-242.

Li X and Orchard M T. New edge-directed interpolation[J]. IEEE Transactions on Image Processing, 2001, 10(10): 1521-1527.

Getreuer P. Contour stencils: total variation along curves for adaptive image interpolation[J]. SIAM Journal on Imaging Sciences, 2011, 4(3): 954-979.

Sun J, Sun J, Xu Z B, et al.. Image super-resolution using gradient profile prior[C]. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, Anchorage, USA, 2008, 1: 2471-2478.

计忠平, 方美娥, 王毅刚, 等. 保持边缘特征和增强对比度的图像缩放算法[J]. 中国图象图形学报, 2012, 17(2): 178-182.

Ji Z P, Fang M E, Wang Y G, et al.. Edge-preserving and contrast-enhance image scaling[J]. Journal of Image and Graphi, 2012, 17(2): 178-182.

杜月林, 韩小萱. 基于边缘检测的图像超分辨率重建研究[J]. 国外电子测量技术, 2012, 31(10): 22-26.

Du Yue-lin and Han Xiao-xuan. The research of super-resolution image reconstruction based on edge detection[J]. Foreign Electronic Measurement Technology, 2012, 31(10): 22-26.

Osher S J and Rudin L I. Feature oriented image enhancement using shock filters[J]. Journal on Numerical Analysis, 1990, 27(4): 919-940.

Alvarez L and Mazorra M. Signal and image restoration using shock filters and anisotropic diffusion[J]. Journal on Numerical Analysis, 1994, 31(2): 590-605.

Starck J L, Moudden Y, Bobin J , et al.. Morphological component analysis[J]. Proceedings of the SPIE, 2005, 5914: 209-223.

肖进胜, 冯慧, 易本顺, 等. 半线性抛物型微分包含的有限差分法[J]. 武汉大学学报(理学版), 2006, 52(3): 262-266.

Xiao Jin-sheng, Feng Hui, Yi Ben-shun, et al.. Finite difference method for semi linear parabolic differential inclusions[J]. Journal of Wuhan Vniversity (Natural Science Edition), 2006, 52(3): 262-266.

施引文献

资源附件(0)

访问统计