Processing astro-photographs using Retinex based methods

D. Marini, C. Bonanomi, A. Rizzi
{"title":"Processing astro-photographs using Retinex based methods","authors":"D. Marini, C. Bonanomi, A. Rizzi","doi":"10.2352/ISSN.2470-1173.2016.6.RETINEX-023","DOIUrl":null,"url":null,"abstract":"Stars, galaxies and some nebulae emit light, differently from solar system planets and satellites that mainly reflect Sun’s light or nebulae that also partly reflect nearby stars light. Light emission is concentrated on specific wavelengths corresponding to transition states of atoms that compose the object. Professional photographers and astronomers use special narrow band filters to detect spectral light emission. Using monochromatic CCD cameras a multi filter photograph can be taken, producing at least long, middle and short wavelength snapshots that can be processed to give full color pictures. Amateurs can use wide-band filters or even color cameras. Colors in astrophotography do not correspond to perceivable colors by human vision system (HVS) and our visual system did not evolve to perceive these kinds of images. Any way we still have to consider our perception when creating pictures to observe cosmic objects photos, that have been rendered using the so called representative colors, selected to show the captured wavelength bands with the purpose to make visible what is scientifically relevant. The typical application field of the Retinex based algorithms is that of natural images, since their purpose is to simulate some behaviors of the human visual system. However we can use HVS properties to enhance astrophotographs and increase local contrast, thus allowing researchers to detect non-visible structures and lay people to be fascinated by richness of cosmic objects. We will present the results of applications of some Retinex based algorithms to astrophotographs. We will discuss their efficacy, compared to traditional methods and discuss possible developments. Introduction Since the launch of Hubble telescope (1990), the first out of atmosphere orbiting telescope, a large amount of new photographs of deep sky objects have been acquired for scientific research purpose and public distribution. A famous picture that contributed to diffuse discoveries of the structure of the universe is the socalled Pillars of Creation in the Eagle nebula Messier 16 (see figure 1 – downloaded from [1]). Let’s explain this image. The staircase structure is due to the structure of Hubble telescope camera system, WFPC-2 (Wide Field/Planet Camera-2 wiffpick) [2], composed of 4 cameras, the top right one having double resolution to observe details of planets, to be down scaled to compose the large field picture. The second observation is the peculiar color channels distribution. The image has been captured through three narrow band filters centered around the emission lines of specific atoms of gas molecules of nebulae: O III (Oxygen III, 501.2 nm Δλ 2.7 nm), Hα (Hydrogen alpha, 656.4 nm Δλ 3.5 nm) and SII (Sulfur II, 673.2 nm Δλ 4.72nm). If we interpret these wavelengths as color bands we see that there is no blue component: OIII is around green and SII, Hα are in the orange-red interval. To explore this color rendering we have downloaded the three band pictures from Hubble Telescope repository [3] and processed for color display creating what in astronomer jargon is a “representative color”, not to be confused with the arbitrary “false color” [4]. The three sub-images in figure 2 have been obtained by assigning channels as Sulfur to red, Hydrogen to green and Oxygen to blue (S=R, H=G, O=B). The second sub-image has been obtained exchanging Hydrogen with Sulfur (H=R, S=G, O=B) and the third sub-image is the assignment O=R, S=G and H=B. Color rendering vary largely among the three distributions and with respect to figure1. We note that the left sub-image of figure 2 (where the color distribution among channels is the common one) is quite different from the one published in hubblesite.org (figure 1). First of all, the mosaic of the four tiles must be aligned, secondly, the colors have been corrected and third the contrast improved. Color correction and contrast improvement are necessary to increase the display of information for the scientist, rather than to obtain beautiful or natural images. They are necessary not to make the pictures more beauty, rather to empower the efficacy of information display for scientist to better understand the nature and structure of the cosmic object and get all the subtleties of the gas distribution. Normally astronomers use GIMP, Photoshop or similar programs for these operations and sometime they use the “false colors” in order to show structures that would be otherwise invisible, thus exploiting different contrast adjustments at different wavelengths. The issues we are facing here, concern the display of complex information, rather than the perception of natural scene (even if astronomical). Our aim is therefore to apply concept of color vision to these kinds of images and to verify if the adoption of algorithms derived from the Retinex theory can provide better results, with less lengthy trial and error work. The same problem applies also to astro-photographs taken with amateur telescopes using color camera rather than monochromatic camera with filters. Retinex algorithms are spatial color algorithms (SCA) [5] inspired by the HVS behavior. They attempt to extract the maximum visual information from images, whose acquisition process and context are unknown. Research has shown that SC algorithms generate the final appearance of an image starting from very poor images in terms of dynamic range, contrast and chromatic content. Mimicking HVS, whose retina has a large overlap between long and medium wavelengths (causing a low L/M ratio), SC algorithms are able to perform an unsupervised enhancement that recovers important visual information from poor input, processing independently the three channels. In some astronomical photographs information about the incoming radiance could be available or approximated from known characteristics of the emitting source (radiance, chromaticity) and the imaging system, but in most cases photographs are not calibrated in the sense that to each digit does not correspond a known invertible function of the radiance. This could be achievable with radiometric measurements, but radiometry is not used for viewing astronomic images. When cosmic object visual rendering is required the purpose of the astronomer is to display some relevant information making it clearly distinguishable. In this case HVS/SCA contrast enhancement has been proved to be effective [6]. Moreover we note that processing color channels independently increases the possibility to maximize the visual information in each channel without adding any cross correlation during processing. The idea of applying HVS inspired method to process astrophotographs is not new, but at our knowledge very few experiences have been presented. The Retinex method proposed in [7] has been applied to natural photographs, a single example of a photo of the Moon is presented in this site: http://dragon.larc.nasa.gov/retinex/Lunar_Orbiter/. Based on the same algorithms as in [7], F. Weinhaus has implemented a Retinex tool into ImageMagick processing function library [8]. Similar tools like e.g. STRESS [9] are also included in the GIMP program and sometimes used for processing astrophotographs. The use of Retinex is also discussed in forums about the image-processing program StarTools by Ivo Jager, who claims to be using Retinex: “The Dynamic range optimization in StarTools is based on a Retinex & Local Histogram Stretching hybrid algorithm” [10]. Gupta and Mandal in [11] consider Retinex as a processing technique to enhance histograms in astrophotographs but we could not find any effective example. A method to estimate fractional gradient to stretch the histogram has been proposed by Sparavigna et al. [12] and tested on some astronomic photographs. To conclude this short review we note that no specific research on HVS inspired methods for processing astro-photographs seems to have been published. In the section Instruments and Methods we will briefly describe the selected algorithms, details are left to the literature, we also identify three kinds of astronomical photographs that show different features relevant for the SCA processing. Moreover we recall the main steps from the astro photo to the SCA processing. In section Experiment Results we present and discuss the results obtained for the chosen astro-photographs and algorithms. In Conclusions we will discuss the results and we will outline possible future developments for making practical SCA processing for astro imaging. Instruments and Methods First of all it is worth to note the characteristics of astronomical images. In natural images we can have extended areas of constant or slowly varying color and contrast, we can have a relationship between a background and a foreground with out of focus regions. Edges in natural images correspond to different objects with some regular on at least known shape. In astro photography we have a huge amount of point sources (the stars). Stars can appear as standalone high luminous points or dense or sparse cluster; they can be aggregated around galaxies or be surrounded by gas nebulae. Galaxies have an irregular light distribution, while nebulae can show more slow varying contrast and luminosity in the different spectral bands. There is no foreground-background relationship and the image field is at the same focus. Most galaxy and nebulae images frequently do not have clear edges. These characteristics of astro images are important to understand how critical is the problem of noise, of contrast and of color rendering to make visible important information. In other words: to prepare the image for the further task of recognition and interpretation. The first step in our work has been therefore to select representative images of the different kinds of deep sky objects and, second, to compare the efficacy of the chosen Retinex algorithms. 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引用次数: 4

Abstract

Stars, galaxies and some nebulae emit light, differently from solar system planets and satellites that mainly reflect Sun’s light or nebulae that also partly reflect nearby stars light. Light emission is concentrated on specific wavelengths corresponding to transition states of atoms that compose the object. Professional photographers and astronomers use special narrow band filters to detect spectral light emission. Using monochromatic CCD cameras a multi filter photograph can be taken, producing at least long, middle and short wavelength snapshots that can be processed to give full color pictures. Amateurs can use wide-band filters or even color cameras. Colors in astrophotography do not correspond to perceivable colors by human vision system (HVS) and our visual system did not evolve to perceive these kinds of images. Any way we still have to consider our perception when creating pictures to observe cosmic objects photos, that have been rendered using the so called representative colors, selected to show the captured wavelength bands with the purpose to make visible what is scientifically relevant. The typical application field of the Retinex based algorithms is that of natural images, since their purpose is to simulate some behaviors of the human visual system. However we can use HVS properties to enhance astrophotographs and increase local contrast, thus allowing researchers to detect non-visible structures and lay people to be fascinated by richness of cosmic objects. We will present the results of applications of some Retinex based algorithms to astrophotographs. We will discuss their efficacy, compared to traditional methods and discuss possible developments. Introduction Since the launch of Hubble telescope (1990), the first out of atmosphere orbiting telescope, a large amount of new photographs of deep sky objects have been acquired for scientific research purpose and public distribution. A famous picture that contributed to diffuse discoveries of the structure of the universe is the socalled Pillars of Creation in the Eagle nebula Messier 16 (see figure 1 – downloaded from [1]). Let’s explain this image. The staircase structure is due to the structure of Hubble telescope camera system, WFPC-2 (Wide Field/Planet Camera-2 wiffpick) [2], composed of 4 cameras, the top right one having double resolution to observe details of planets, to be down scaled to compose the large field picture. The second observation is the peculiar color channels distribution. The image has been captured through three narrow band filters centered around the emission lines of specific atoms of gas molecules of nebulae: O III (Oxygen III, 501.2 nm Δλ 2.7 nm), Hα (Hydrogen alpha, 656.4 nm Δλ 3.5 nm) and SII (Sulfur II, 673.2 nm Δλ 4.72nm). If we interpret these wavelengths as color bands we see that there is no blue component: OIII is around green and SII, Hα are in the orange-red interval. To explore this color rendering we have downloaded the three band pictures from Hubble Telescope repository [3] and processed for color display creating what in astronomer jargon is a “representative color”, not to be confused with the arbitrary “false color” [4]. The three sub-images in figure 2 have been obtained by assigning channels as Sulfur to red, Hydrogen to green and Oxygen to blue (S=R, H=G, O=B). The second sub-image has been obtained exchanging Hydrogen with Sulfur (H=R, S=G, O=B) and the third sub-image is the assignment O=R, S=G and H=B. Color rendering vary largely among the three distributions and with respect to figure1. We note that the left sub-image of figure 2 (where the color distribution among channels is the common one) is quite different from the one published in hubblesite.org (figure 1). First of all, the mosaic of the four tiles must be aligned, secondly, the colors have been corrected and third the contrast improved. Color correction and contrast improvement are necessary to increase the display of information for the scientist, rather than to obtain beautiful or natural images. They are necessary not to make the pictures more beauty, rather to empower the efficacy of information display for scientist to better understand the nature and structure of the cosmic object and get all the subtleties of the gas distribution. Normally astronomers use GIMP, Photoshop or similar programs for these operations and sometime they use the “false colors” in order to show structures that would be otherwise invisible, thus exploiting different contrast adjustments at different wavelengths. The issues we are facing here, concern the display of complex information, rather than the perception of natural scene (even if astronomical). Our aim is therefore to apply concept of color vision to these kinds of images and to verify if the adoption of algorithms derived from the Retinex theory can provide better results, with less lengthy trial and error work. The same problem applies also to astro-photographs taken with amateur telescopes using color camera rather than monochromatic camera with filters. Retinex algorithms are spatial color algorithms (SCA) [5] inspired by the HVS behavior. They attempt to extract the maximum visual information from images, whose acquisition process and context are unknown. Research has shown that SC algorithms generate the final appearance of an image starting from very poor images in terms of dynamic range, contrast and chromatic content. Mimicking HVS, whose retina has a large overlap between long and medium wavelengths (causing a low L/M ratio), SC algorithms are able to perform an unsupervised enhancement that recovers important visual information from poor input, processing independently the three channels. In some astronomical photographs information about the incoming radiance could be available or approximated from known characteristics of the emitting source (radiance, chromaticity) and the imaging system, but in most cases photographs are not calibrated in the sense that to each digit does not correspond a known invertible function of the radiance. This could be achievable with radiometric measurements, but radiometry is not used for viewing astronomic images. When cosmic object visual rendering is required the purpose of the astronomer is to display some relevant information making it clearly distinguishable. In this case HVS/SCA contrast enhancement has been proved to be effective [6]. Moreover we note that processing color channels independently increases the possibility to maximize the visual information in each channel without adding any cross correlation during processing. The idea of applying HVS inspired method to process astrophotographs is not new, but at our knowledge very few experiences have been presented. The Retinex method proposed in [7] has been applied to natural photographs, a single example of a photo of the Moon is presented in this site: http://dragon.larc.nasa.gov/retinex/Lunar_Orbiter/. Based on the same algorithms as in [7], F. Weinhaus has implemented a Retinex tool into ImageMagick processing function library [8]. Similar tools like e.g. STRESS [9] are also included in the GIMP program and sometimes used for processing astrophotographs. The use of Retinex is also discussed in forums about the image-processing program StarTools by Ivo Jager, who claims to be using Retinex: “The Dynamic range optimization in StarTools is based on a Retinex & Local Histogram Stretching hybrid algorithm” [10]. Gupta and Mandal in [11] consider Retinex as a processing technique to enhance histograms in astrophotographs but we could not find any effective example. A method to estimate fractional gradient to stretch the histogram has been proposed by Sparavigna et al. [12] and tested on some astronomic photographs. To conclude this short review we note that no specific research on HVS inspired methods for processing astro-photographs seems to have been published. In the section Instruments and Methods we will briefly describe the selected algorithms, details are left to the literature, we also identify three kinds of astronomical photographs that show different features relevant for the SCA processing. Moreover we recall the main steps from the astro photo to the SCA processing. In section Experiment Results we present and discuss the results obtained for the chosen astro-photographs and algorithms. In Conclusions we will discuss the results and we will outline possible future developments for making practical SCA processing for astro imaging. Instruments and Methods First of all it is worth to note the characteristics of astronomical images. In natural images we can have extended areas of constant or slowly varying color and contrast, we can have a relationship between a background and a foreground with out of focus regions. Edges in natural images correspond to different objects with some regular on at least known shape. In astro photography we have a huge amount of point sources (the stars). Stars can appear as standalone high luminous points or dense or sparse cluster; they can be aggregated around galaxies or be surrounded by gas nebulae. Galaxies have an irregular light distribution, while nebulae can show more slow varying contrast and luminosity in the different spectral bands. There is no foreground-background relationship and the image field is at the same focus. Most galaxy and nebulae images frequently do not have clear edges. These characteristics of astro images are important to understand how critical is the problem of noise, of contrast and of color rendering to make visible important information. In other words: to prepare the image for the further task of recognition and interpretation. The first step in our work has been therefore to select representative images of the different kinds of deep sky objects and, second, to compare the efficacy of the chosen Retinex algorithms. Image Selection The images selection has been driven by the necessity to consider different kinds of sky
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使用基于Retinex的方法处理天文照片
恒星、星系和一些星云会发光,而太阳系的行星和卫星主要反射太阳的光,而星云也会部分反射附近恒星的光。光发射集中在与组成物体的原子的过渡态相对应的特定波长上。专业摄影师和天文学家使用特殊的窄带滤光片来探测光谱发射。使用单色CCD相机可以拍摄多滤镜照片,至少可以产生长、中、短波长的快照,这些快照可以处理成全彩照片。业余爱好者可以使用宽频带滤镜,甚至彩色相机。天体摄影中的颜色与人类视觉系统(HVS)可感知的颜色不一致,我们的视觉系统没有进化到可以感知这些类型的图像。无论如何,我们在拍摄观察宇宙物体的照片时仍然要考虑我们的感知,这些照片是用所谓的代表性颜色渲染的,选择用来显示捕获的波长带,目的是使科学相关的东西可见。基于Retinex的算法的典型应用领域是自然图像,因为它们的目的是模拟人类视觉系统的一些行为。然而,我们可以使用HVS属性来增强天体照片并增加局部对比度,从而使研究人员能够探测到不可见的结构,并使外行人着迷于丰富的宇宙物体。我们将介绍一些基于Retinex的算法在天体照片中的应用结果。我们将讨论它们的功效,与传统方法相比,并讨论可能的发展。自哈勃望远镜(1990年)发射以来,第一个大气层外轨道望远镜获得了大量新的深空天体照片,用于科学研究和公众传播。在鹰状星云梅西耶16中所谓的“创造之柱”(见图1 -从[1]下载)是一幅著名的图片,它有助于对宇宙结构的广泛发现。让我们来解释一下这个图像。阶梯式结构是由于哈勃望远镜相机系统WFPC-2 (Wide Field/Planet camera -2 wiffpick)[2]的结构,该系统由4台相机组成,右上方的相机具有双分辨率,可以观察行星的细节,然后缩小以组成大视场图像。第二个观察是奇特的颜色通道分布。该图像是通过以星云气体分子特定原子发射线为中心的三个窄带滤波器捕获的:O III(氧III, 501.2 nm Δλ 2.7 nm), Hα(氢α, 656.4 nm Δλ 3.5 nm)和SII(硫II, 673.2 nm Δλ 4.72nm)。如果我们将这些波长解释为色带,我们会发现没有蓝色成分:OIII在绿色附近,而SII、Hα在橙红色区间。为了探索这种显色性,我们从哈勃望远镜存储库[3]中下载了三个波段的图片,并进行了彩色显示处理,创建了天文学家术语中的“代表色”,不要与任意的“假色”[4]混淆。图2中的三个子图像是通过将通道分配为硫为红色,氢为绿色和氧为蓝色(S=R, H=G, O=B)而获得的。得到氢与硫(H=R, S=G, O=B)交换的第二副图像,得到O=R, S=G, H=B的第三副图像。三种分布之间的显色性差异很大,与图1有关。我们注意到,图2的左子图像(通道间的颜色分布是共同的)与hubblesite.org上发表的图像(图1)有很大的不同。首先,四个瓷砖的马赛克必须对齐,其次,颜色已经校正,第三,对比度提高。色彩校正和对比度的提高对于科学家来说是必要的,以增加信息的显示,而不是获得美丽或自然的图像。它们不是为了使图片更加美丽,而是为了增强信息显示的功效,以便科学家更好地了解宇宙物体的性质和结构,并获得气体分布的所有微妙之处。通常情况下,天文学家使用GIMP、Photoshop或类似的程序进行这些操作,有时他们使用“假色”来显示否则看不见的结构,从而利用不同波长下不同的对比度调整。我们在这里面临的问题,是复杂信息的显示,而不是对自然场景的感知(即使是天文数字)。因此,我们的目标是将色彩视觉的概念应用于这些类型的图像,并验证采用来自视网膜理论的算法是否可以提供更好的结果,减少长时间的试验和错误工作。 同样的问题也适用于业余天文望远镜用彩色相机而不是带滤镜的单色相机拍摄的天文照片。Retinex算法是受HVS行为启发的空间颜色算法(SCA)[5]。他们试图从图像中提取最大的视觉信息,这些图像的获取过程和背景是未知的。研究表明,SC算法从动态范围、对比度和色彩内容非常差的图像开始生成图像的最终外观。模仿HVS,其视网膜在长波和中波之间有很大的重叠(导致低L/M比),SC算法能够执行无监督增强,从差的输入中恢复重要的视觉信息,独立处理三个通道。在一些天文照片中,可以从发射源的已知特性(辐射度、色度)和成像系统获得或近似获得关于入射辐射的信息,但在大多数情况下,照片没有校准,因为每个数字不对应于已知的辐射的可逆函数。这可以通过辐射测量来实现,但辐射测量不用于观测天文图像。当需要对宇宙物体进行视觉渲染时,天文学家的目的是显示一些相关信息,使其清晰可辨。在这种情况下,HVS/SCA对比度增强已被证明是有效的[6]。此外,我们注意到独立处理颜色通道增加了在处理过程中不添加任何相互关联的情况下最大化每个通道中的视觉信息的可能性。应用HVS启发的方法来处理天文照片的想法并不新鲜,但据我们所知,很少有经验被提出。[7]中提出的Retinex方法已经应用于自然照片,这个网站提供了一张月球照片的例子:http://dragon.larc.nasa.gov/retinex/Lunar_Orbiter/。F. Weinhaus基于与[7]相同的算法,在ImageMagick处理函数库中实现了一个Retinex工具[8]。类似的工具,如STRESS[9]也包括在GIMP程序中,有时用于处理天文照片。在关于图像处理程序StarTools的论坛上,Ivo Jager也讨论了Retinex的使用,他声称正在使用Retinex:“StarTools中的动态范围优化是基于Retinex和局部直方图拉伸混合算法”[10]。Gupta和Mandal在[11]中认为Retinex是一种增强天文照片中直方图的处理技术,但我们找不到任何有效的例子。Sparavigna等人[12]提出了一种估算分数梯度来拉伸直方图的方法,并在一些天文照片上进行了测试。在总结这篇简短的评论时,我们注意到,似乎没有发表过关于HVS启发的处理天文照片方法的具体研究。在仪器和方法一节中,我们将简要描述所选择的算法,细节留给文献,我们还确定了三种天文照片,它们显示了与SCA处理相关的不同特征。此外,我们回顾了从天文照片到SCA处理的主要步骤。在实验结果一节中,我们介绍并讨论了所选天文照片和算法的结果。在结论中,我们将讨论这些结果,并概述未来可能的发展,使实际的SCA处理用于天文成像。仪器和方法首先,天文图像的特点值得注意。在自然图像中,我们可以有恒定或缓慢变化的颜色和对比度的扩展区域,我们可以有一个背景和前景之间的关系与失焦区域。自然图像中的边缘对应不同的物体,至少在已知的形状上有一些规则。在天文摄影中,我们有大量的点光源(星星)。恒星可以是独立的高亮点,也可以是密集或稀疏的星团;它们可以聚集在星系周围,也可以被气体星云包围。星系的光分布是不规则的,而星云在不同的光谱波段可以表现出更缓慢的对比度和光度变化。没有前景和背景的关系,图像场在同一焦点上。大多数星系和星云图像经常没有清晰的边缘。天文图像的这些特征对于理解噪声问题、对比度问题和色彩渲染问题是多么重要,从而使重要信息可见是非常重要的。换句话说:为进一步的识别和解释任务准备图像。因此,我们工作的第一步是选择不同类型深空物体的代表性图像,其次是比较所选择的Retinex算法的有效性。 图像的选择是由于需要考虑不同种类的天空
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