Super resolution of aerial image by means of polyphase components reconstruction

	Super resolution of aerial image by means of polyphase components reconstruction
	He, L. Y.; J. H. Liu and G. Li
	2015
发表期刊	Acta Physica Sinica
卷号	64 期号:11 页码:8
摘要	Multi-frame super resolution reconstruction is a technology for obtaining a high resolution image from a set of blurred and aliased low resolution images. The most popular and widely used super resolution methods are motion based. However, the estimation of motion information (registration) is very difficult, computationally expensive and inaccurate, especially for aerial image. The sub-pixel registration error restricts the performance of the subsequent super resolution. Instead of trying to parameterize the motion estimation model, this paper proposes an image super resolution framework based on the polyphase components reconstruction algorithm and an improved steering kernel regression algorithm. Given an image observation model, a reversible 2D polyphase decomposition, which breaks down a high resolution image into polyphase components, is obtained. Though the assumption of diversity sampling, this paper adopts a fundamentally different approach, in which the low-resolution frames is used as the basis and the reference frame as the reference subpolyphase component of the high resolution image for recovering the polyphase components of the high resolution image. The polyphase components, which fuse the low resolution frames with the complementary details, can be obtained by computing their expansion coefficients in terms of this basis using the available sub-polyphase components and then inversely transforming them into a high resolution image. This paper accomplishes this by formulating the problem as the maximum likelihood estimation, which guarantees a close-to-perfect solution. Furthermore, this paper proposes an improved steering kernel regression algorithm, to help restore the fusion image with mild blur and random noise. This paper adaptively refines the steering kernel regression function according to the local region context and structures. Thus, this new algorithm not only effectively combines denoising and deblurring together, but also preserves the edge information. Our framework develops an efficient and stable algorithm to tackle the huge size and ill-posedness of the super resolution problem, and improves the computational efficiency via avoiding registration and iterative computation. Several experimental results on synthetic data illustrate that our method outperforms the state-of-the-art methods in quantitative and qualitative comparisons. The proposed super resolution algorithm can indeed reconstruct high-frequency information which is otherwise unavailable in the single LR image. It can effectively suppress blur and noise, and produce visually pleasing resolution enhancement in aerial images.
收录类别	SCI ; EI
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/55546
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	He, L. Y.,J. H. Liu and G. Li. Super resolution of aerial image by means of polyphase components reconstruction[J]. Acta Physica Sinica,2015,64(11):8.
APA	He, L. Y.,&J. H. Liu and G. Li.(2015).Super resolution of aerial image by means of polyphase components reconstruction.Acta Physica Sinica,64(11),8.
MLA	He, L. Y.,et al."Super resolution of aerial image by means of polyphase components reconstruction".Acta Physica Sinica 64.11(2015):8.

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基于多相组重建的航空图像超分辨率算法.p（786KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载