基于计算光学的简单透镜成像技术

	基于计算光学的简单透镜成像技术
其他题名	Imaging though simple lens based on computational photography
	郝建坤
学位类型	硕士
导师	黄玮
	2015-11
学位授予单位	中国科学院大学
学位专业	光学
关键词	计算光学图像复原简单透镜成像空间变化psf 去卷积
摘要	现代成像光学系统一般通过增加光学元件数量、引入非球面甚至自由曲面来消除系统像差，提高像质。这将导致光学系统复杂度增加，系统加工难、造价高，并且受装调、工艺、重量等因素的限制。在保证系统成像质量的前提下，为简化光学系统复杂度，提出基于计算光学的简单透镜成像技术。将光学与飞速发展的计算机技术相结合，通过图像处理技术对简单透镜系统所成模糊图像进行复原，重构清晰图像，提高像质。传统图像复原法大多基于光学系统点扩散函数空间不变的假设上，实际光学系统由于像差的影响，点扩散函数随视场的变化而变化。本文基于空间变化的PSF，对现有的稀疏先验去卷积算法进行改进，提出可变参数的稀疏先验非盲去卷积算法，并对图像进行复原。文章的主要内容为：首先，对光学系统点扩散函数空间变化特性进行分析，提出两种空间变化PSF获取方法：一种在进行光学系统设计过程中，提取系统空间变化PSF并进行算法预处理，保留有效信息；第二种通过仪器测量光学系统的LSF，根据PSF与LSF、MTF三者之间的关系，通过算法进行计算，最终利用插值拟合的方式得到整幅图像空间变化的PSF。其次，将模糊图像重叠分块，每个子图像块用不同的PSF对其去卷积进行重构。自然图像梯度满足稀疏分布，在去卷积算法中引入稀疏先验作为正则项，并将代表图像梯度稀疏度的参数作为可变值，利用迭代重加权最小二乘法(IRLS)，在迭代过程中使复原图像梯度分布更趋近于真实值，同时避免图像过度平滑。采用重叠分块复原的方法，能够有效减小图像拼接处的振铃效应，并在图像融合时对图像重叠区域使用图像平均处理法,使图像更加平滑。最后，为验证算法的有效性，对简单透镜系统进行数字仿真实验。搭建实验平台，测量单透镜空间变化PSF，并对其模糊图像进行复原，重构出清晰图像，进一步验证了基于计算光学提高简单透镜成像像质算法的有效性。实验结果表明，本文提出的算法对简单透镜光学系统所成图像有较好的复原效果，其像质得到提升。
其他摘要	Modern imaging optical system generally by increasing the number of optical elements, introducing non-spherical surface even the freeform suface to eliminate system aberrations and improve image quality. This will lead to the optical system complexity increased , processing difficult and high cost, and it is also limited to alignment, technology, weight and other factors. In order to simplify the complexity of the optical system, a simple lens imaging technique based on computational photography is proposed, which is under the premise of ensuring the quality of the system. Combining optics with computer technology which is rapidly developed, through the image processing technology to restore blur images imaging with simple lens, reconstruct clear images and improve image quality. The conventional image restoration method is based on the assumption that the point spread function(PSF) of optical system is space-invariant, but the actual optical system because of the influence of aberrations, the PSF is changed with the field of view. In this paper, making an improvement on the existing sparse prior deconvolution algorithm, and proposing the variable parameter of the sparse prior non-blind deconvolution algorithm, and the image restoration. The main contents of the article as follows: First, the space variation characteristics of the optical system point spread function were analyzed, and put forward two acquisition methods of space-varying PSF. One is extracting in the process of optical system design, preprocessing by algorithm and retaining effective information. The second method is measuring the LSF of optical system through instrument, then caculate the PSF by algorithm according to the relations among the LSF, MTF and PSF. At last the way of interpolation are used to get spatially-varying PSF of the whole image. Second, blocking the blurred image overlapped, and each piece of image deconvolution with different PSF. Natural image gradients meet the sparse distribution, introducing sparse priors as a regularization term in deconvolution algorithm, setting the parameter which representing the image gradient sparsity as a variable value, and using iterative reweighted least squares (IRLS) to deconvolve a image. The gradient of recovered image in the iterative process is closer to a true gradient distribution, while avoiding excessive smoothing of image. The overlapped block restoration method can effectively reduce the ringing artifacts in image stitching. Image average method is used in image overlap region to make the image smoother when spliting the image. Finally, to verify the effectiveness of the algorithm, a digital simulation experiment is carried out on the simple lens system. The experimental platform is set up to measure the spatial variation PSF of a single lens, and the blurred image is reconstructed. The validity of the algorithm based on computational photography to improve image quality through simple lens is further verified Experimental results show that the proposed algorithm has good recovery effect on the simple lens optical system, and the image quality has been improved.
语种	中文
文献类型	学位论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/49231
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	郝建坤. 基于计算光学的简单透镜成像技术[D]. 中国科学院大学,2015.

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