星空场景的手机拍摄方法
发布时间：2019-02-16 02:41
【摘要】：智能手机在日常生活中的使用已经相当普遍,一些高端智能手机的相机像素也已经达到甚至超过了数码相机的像素。随着软件智能化和硬件微型化水平的不断发展,人们对智能手机拍照功能的要求也日益提高。在这种情况下,特殊场景如星空、闪电和烟花等场景的拍照模式成为了众厂商在智能手机摄像上研究的重点方向,也是竞争相当激烈的一个新兴的发展领域。传统的星空拍摄采用单次长曝光法,但是受到电池电量和热噪的影响,已经逐步被叠加法取代,该方法采用较高的感光度,较大的光圈,较长的曝光时间,连续拍摄多张照片,然后用后处理算法进行叠加合成绚丽的星空。因此,如何克服高感光度带来的噪声,较长曝光时间引入的模糊,达到完美的多帧合成效果都是手机拍摄星空所面临的问题。本文根据现今的手机对焦策略,采用基于图像的自动对焦方法,利用拉普拉斯算子作为评价函数,极点搜索法作为搜索策略进行自动对焦。在拍照过程中,针对相机和星空场景的相对运动而导致的图像模糊问题,采用了一种新的针对星空图像的运动模糊复原算法。首先采用一种改进的细化算法得到星空图像的星点运动轨迹,从而提取出星空运动模糊图像的模糊核,然后基于Richardson-Lucy的复原算法对模糊图像进行复原。实验结果表明,本文采用的利用细化算法得到模糊核的方法复杂度低,耗时少且准确性高,对于星空图像的运动模糊具有很好的复原效果。光照不足的条件下,针对开启高感光度引入的高感光度噪声问题,本文采用基于均值加速的快速中值滤波对星空图像进行去噪,实验结果表明这种方法不仅时间复杂度低,还能有效的去除星空图像中的高感光度噪声。为了能够捕捉到不同状态下,如亮暗不同、闪烁变化的星点,采用基于特征点的方法对星空图像进行了图像配准,在星空图像配准的前提下,根据星点的特点,利用像素值取大的融合方法对星空场景模拟图像进行多帧融合。该方法复杂度较低且效果较好,最终高效的获得了完美的多帧融合后星空图像。针对手机在星空场景拍摄中出现的问题,本文旨在提出一种合理的解决方案,并在实验室模拟实现相关算法。本文对于自动对焦、手机抖动导致的运动模糊复原、星空图像高感光度去噪以及星空图像的配准融合四个方面的问题进行了深入研究以及不同算法的对比实验,模拟星空场景拍摄的实验结果表明,经过本文一系列星空场景算法的处理,最终能够获得清晰完美的星空图像。
[Abstract]:The use of smart phones in daily life is already quite common, and some high-end smartphones have camera pixels that have reached or even exceeded those of digital cameras. With the development of software intelligence and hardware miniaturization, the requirement of smart phone photo-taking is increasing. In this case, the photography mode of special scenes such as starry sky, lightning and fireworks has become the focus of research on smartphone camera, and it is also a new field of development in which the competition is very fierce. Traditional star photography uses single long exposure method, but it has been replaced by superposition method because of the influence of battery power and thermal noise. This method uses higher sensitivity, larger aperture, longer exposure time, and takes many pictures continuously. Then the post-processing algorithm is used to superposition and synthesize the brilliant star sky. Therefore, how to overcome the noise caused by high luminosity, the blur introduced by long exposure time, and achieve the perfect multi-frame synthesis effect are the problems that the mobile phone faces in shooting star sky. In this paper, according to the present mobile phone focusing strategy, the image based auto-focusing method is adopted, Laplace operator is used as the evaluation function, and the pole search method is used as the search strategy. In order to solve the problem of image blur caused by the relative motion of camera and star scene, a new motion blur restoration algorithm for star-sky images is proposed in this paper. Firstly, an improved thinning algorithm is used to obtain the star motion trajectory of the star image, and then the blur kernel of the star motion blur image is extracted, and then the blur image is restored based on the Richardson-Lucy algorithm. The experimental results show that the proposed thinning algorithm has the advantages of low complexity, less time consuming and high accuracy, and has a good restoration effect for the motion blur of star images. Under the condition of insufficient illumination, aiming at the problem of high sensitivity noise caused by opening high sensitivity, this paper uses a fast median filter based on mean acceleration to Denoise the star image. The experimental results show that this method is not only low in time complexity, but also less complex in time. It can also effectively remove the high luminosity noise in the sky image. In order to capture the star points in different states, such as different brightness and dark, the star image is registered based on the feature point method. Under the premise of the star image registration, according to the characteristics of the star point, The multi-frame fusion method of star scene simulation image is presented in this paper. This method has low complexity and good effect. Finally, the perfect multi-frame fused star image is obtained efficiently. Aiming at the problem of mobile phone shooting in star-sky scene, this paper proposes a reasonable solution and implements the algorithm in laboratory simulation. In this paper, four aspects of automatic focus, mobile phone jitter caused motion blur restoration, star image high sensitivity denoising and star image registration fusion are studied in depth and the contrast experiments of different algorithms are carried out. The experimental results of simulated star scene shooting show that through the processing of a series of star scene algorithms in this paper, a clear and perfect star sky image can be obtained.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP391.41;TB86
本文编号：2423961
[Abstract]:The use of smart phones in daily life is already quite common, and some high-end smartphones have camera pixels that have reached or even exceeded those of digital cameras. With the development of software intelligence and hardware miniaturization, the requirement of smart phone photo-taking is increasing. In this case, the photography mode of special scenes such as starry sky, lightning and fireworks has become the focus of research on smartphone camera, and it is also a new field of development in which the competition is very fierce. Traditional star photography uses single long exposure method, but it has been replaced by superposition method because of the influence of battery power and thermal noise. This method uses higher sensitivity, larger aperture, longer exposure time, and takes many pictures continuously. Then the post-processing algorithm is used to superposition and synthesize the brilliant star sky. Therefore, how to overcome the noise caused by high luminosity, the blur introduced by long exposure time, and achieve the perfect multi-frame synthesis effect are the problems that the mobile phone faces in shooting star sky. In this paper, according to the present mobile phone focusing strategy, the image based auto-focusing method is adopted, Laplace operator is used as the evaluation function, and the pole search method is used as the search strategy. In order to solve the problem of image blur caused by the relative motion of camera and star scene, a new motion blur restoration algorithm for star-sky images is proposed in this paper. Firstly, an improved thinning algorithm is used to obtain the star motion trajectory of the star image, and then the blur kernel of the star motion blur image is extracted, and then the blur image is restored based on the Richardson-Lucy algorithm. The experimental results show that the proposed thinning algorithm has the advantages of low complexity, less time consuming and high accuracy, and has a good restoration effect for the motion blur of star images. Under the condition of insufficient illumination, aiming at the problem of high sensitivity noise caused by opening high sensitivity, this paper uses a fast median filter based on mean acceleration to Denoise the star image. The experimental results show that this method is not only low in time complexity, but also less complex in time. It can also effectively remove the high luminosity noise in the sky image. In order to capture the star points in different states, such as different brightness and dark, the star image is registered based on the feature point method. Under the premise of the star image registration, according to the characteristics of the star point, The multi-frame fusion method of star scene simulation image is presented in this paper. This method has low complexity and good effect. Finally, the perfect multi-frame fused star image is obtained efficiently. Aiming at the problem of mobile phone shooting in star-sky scene, this paper proposes a reasonable solution and implements the algorithm in laboratory simulation. In this paper, four aspects of automatic focus, mobile phone jitter caused motion blur restoration, star image high sensitivity denoising and star image registration fusion are studied in depth and the contrast experiments of different algorithms are carried out. The experimental results of simulated star scene shooting show that through the processing of a series of star scene algorithms in this paper, a clear and perfect star sky image can be obtained.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP391.41;TB86
【参考文献】
相关期刊论文 前1条
1 郑玉珍,吴勇,倪旭翔;实时自动对焦的研究[J];光电工程;2004年04期
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