激光与光电子学进展, 2018, 55 (9): 091004, 网络出版: 2018-09-08   

红外遥感图像TGV正则化超分辨率重建 下载: 754次

TGV Regularized Super Resolution Reconstruction for Infrared Remote Sensing Image
作者单位
郑州升达经贸管理学院应用数学研究所, 河南 郑州 451191
摘要
为了克服图像超分辨重建中四阶全变分正则化模型存在的“斑点”现象和稀疏正则化模型中最优解不唯一的缺点, 结合红外遥感图像超分辨率重建的实际需求, 提出了一种基于总广义变分正则化的红外遥感图像超分辨重建模型。根据零阶张量空间和松弛解的相关概念, 分析了模型的优点和可行性。结合该模型的自身分裂性, 采用交替方向乘数法将模型分裂为两个子问题, 分别利用共轭梯度法和快速傅里叶变换方法进行数值求解。从测试结果分析, 无论是模拟图像还是真实图像利用提出模型重建后的图像分辨率均有明显提升; 客观评价中的不同指标值均优于近期文献中的方法, 其中峰值信噪比提高约2 dB, 信噪比、结构相似度和信息熵分别提高1、0.02和0.1个单位。
Abstract
To overcome the shortcoming of bright speck phenomenon in four order totally variational model and the non-unique optimal solution in sparse regularization model of regularization image super-resolution reconstruction, an infrared remote sensing image super-resolution reconstruction model based on total generalized variation regularization is proposed in combination with the actual demand of infrared remote sensing image super-resolution reconstruction. The advantages and feasibility are analyzed with the concept of zero-order tensor space and the relaxation solution. Combined with the self-fissility of this model, the reconstruction model is split into two sub-problems by alternating direction multiplier method. The conjugate gradient method and the fast Fourier transform method are used to solve the sub-problem in numerical solution process, respectively. From the analysis of the testing results, the proposed model has a significant improvement in the resolution of the reconstructed image for both the simulated image and the real image. The objective evaluation is better than the method used in the literature, in which the peak signal to noise ratio can are increased by 1, 0.02 and 0.1 unit, respectively.

时文俊. 红外遥感图像TGV正则化超分辨率重建[J]. 激光与光电子学进展, 2018, 55(9): 091004. Shi Wenjun. TGV Regularized Super Resolution Reconstruction for Infrared Remote Sensing Image[J]. Laser & Optoelectronics Progress, 2018, 55(9): 091004.

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