| 基于退化模型和邻域嵌套的彩色图像超分辨率自适应重建 |
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| 引用本文： | 杨欣,姜斌,周大可.基于退化模型和邻域嵌套的彩色图像超分辨率自适应重建[J].东南大学学报(自然科学版),2011,41(6):1193-1196. |
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| 作者姓名： | 杨欣 姜斌 周大可 |
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| 作者单位： | 1. 南京航空航天大学自动化学院,南京210016;北京师范大学遥感科学国家重点实验室,北京100875
2. 南京航空航天大学自动化学院,南京,210016 |
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| 基金项目： | 国家自然科学基金资助项目，高等学校博士学科点专项科研基金资助项目，中国科学院遥感应用研究所、北京师范大学遥感科学国家重点实验室开放基金资助项目，南京航空航天大学基本科研业务费专项科研资助项目 |
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| 摘 要： | 为有效提升图像质量,提出一种基于图像退化模型和邻域嵌套的彩色图像超分辨率重建算法.通过退化模型在彩色空间上得出图像超分辨率重建训练集,并根据此训练集进行图像邻域分块.为了在训练过程中抑制噪声并锐化图像中的边缘信息,提取训练集亮度和梯度特征并进行特征融合.为了有效提升重建算法的自适应性,引入图像重建优化参数和边缘信息参数...
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| 关 键 词： | 超分辨率重建 退化模型 邻域嵌套 特征提取 |
Degradation model and neighbor embedding based color image adaptive super-resolution reconstruction |
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| Yang Xin,Jiang Bin,Zhou Dake.Degradation model and neighbor embedding based color image adaptive super-resolution reconstruction[J].Journal of Southeast University(Natural Science Edition),2011,41(6):1193-1196. |
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| Authors: | Yang Xin Jiang Bin Zhou Dake |
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| Institution: | 1(1 College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)(2 National Laboratory on Machine Perception,Beijing Normal University,Beijing 100875,China) |
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| Abstract: | A new color image super-resolution reconstruction method base on degradation model and neighbor embedding is proposed to effectively improve the image quality.Through image degradation model training set is obtained in color space and then according to this set the image area is cut into patches.A new combination of features is proposed based on luminance and gradient,which can preserve edges and smoothen color regions.Then image super-resolution optimization parameter(SOP) and edge information parameter(EIP) are introduced in order to effectively enhance the adaption of the algorithm and according to which,SR(super-resolution) model is given.Finally,the specific process of patches by Least Squares method is obtained.And the patches are stitched according to the corresponding coordinates,where the overlapping regions of patches are averaged.Experiments show that the proposed algorithm performs better in both quantitative and qualitative evaluation. |
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| Keywords: | super-resolution reconstruction degradation model neighbor embedding feature extraction |
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