L1-norm-based Image Super-resolution and Its Differential Statistical Model

doi:10.3969/j.issn.1000-3428.2007.24.071

Computer Engineering ›› 2007, Vol. 33 ›› Issue (24): 203-205. doi: 10.3969/j.issn.1000-3428.2007.24.071

• Artificial Intelligence and Recognition Technology • Previous Articles Next Articles

L1-norm-based Image Super-resolution and Its Differential Statistical Model

YI Hai-lun, WANG Qing

School of Computer, Northwestern Polytechnical University, Xi’an 710072

Received:1900-01-01 Revised:1900-01-01 Online:2007-12-20 Published:2007-12-20

基于L1范数的图像超分辨率及差分统计模型

倚海伦，王庆

西北工业大学计算机学院，西安 710072

Abstract

Abstract: A method for automatically estimating parameters is applied to the L1-norm-based image super-resolution reconstruction framework. The approach can get a stable result with model errors and can improve convergence. A novel explanation of L1-norm-based bilateral total variation(BTV) term is presented according to pixel differences statistics, combined with probability prior model. Superiority of BTV is validated using Kullback-Leibler distance. A theoretical analysis of the feasibility and the problems of super-resolution reconstruction are given using mixture prior distribution.

Key words: super-resolution, regularization, pixel difference image

摘要： 在L1范数图像超分辨率重建框架下，引入参数自适应估计，该方法对模型误差表现出良好的稳健性并且可以加速收敛。结合差分图像统计特性和概率先验模型，解释了L1范数形式的双边全变差正则项概念，利用Kullback-Leibler距离证明了该正则项的优越性，并分析了混合先验模型在超分辨率重建中应用的可行性等问题。

关键词: 超分辨率, 正则化, 差分图像

CLC Number:

TP18

YI Hai-lun; WANG Qing. L1-norm-based Image Super-resolution and Its Differential Statistical Model[J]. Computer Engineering, 2007, 33(24): 203-205.

倚海伦;王庆. 基于L1范数的图像超分辨率及差分统计模型[J]. 计算机工程, 2007, 33(24): 203-205.

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