单帧图像超分辨中的自适应正则约束算法

摘要/Abstract

摘要： 单帧图像超分辨作为一个典型的欠定问题,在优化求解过程中需要引入正则项进行约束,以提高超分辨重建的稳定性。平滑性正则作为超分辨中的一种常用正则项,容易导致图像高频信息丢失,造成图像中的边缘部分模糊,影响重建图像的视觉效果。利用马尔科夫随机场(Markov Random Field,MRF)对局部图像进行建模,表征了局部图像块内像元间的相关关系,并基于此实现了超分辨过程中的自适应正则约束,有效避免了图像边缘等位置的模糊效应,提高了图像的重建性能。

关键词: 单帧图像超分辨, 马尔科夫随机场, 自适应

Abstract: As a typical undetermined problem,super-resolution of single-frame images needs to be constrained by regular terms in the process of optimization,so as to improve the stability of super-resolution reconstruction.As a regular term commonly used in super-resolution,smoothness regularities may lead to the loss of high frequency information in images,cause the blurring of marginal areas in images,and affect the visual effects of reconstructed images.Based on Markov random field(MRF),this paper built the model of local image,characterized the correlation between the pixels in the local image block and realized self-adapting regular constraint in the process of super-resolution,which can effectively avoid the blurring effect in the marginal areas and other positions in the images,and improve the performance of the image reconstruction.

Key words: Markov random field, Self-adapting, Super-resolution of single-frame images

中图分类号:

TP751

黎海雪, 林海涛, 陈津. 单帧图像超分辨中的自适应正则约束算法[J]. 计算机科学, 2019, 46(6A): 200-204. https://doi.org/

LI Hai-xue, LIN Hai-tao, CHEN Jin. Self-adapting Regular Constraint Algorithm in Super-resolution of Single-frame Images[J]. Computer Science, 2019, 46(6A): 200-204. https://doi.org/

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