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Designator Retinex, Milano Retinex and the locality issue 标志网、米兰网和地方问题
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-018
A. Rizzi
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引用次数: 7
The Oriented Difference-of-Gaussians Model of Brightness Perception 亮度感知的定向差分高斯模型
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-019
M. McCourt, B. Blakeslee, D. Cope
The Oriented Difference of Gaussians (ODOG) model (6) was developed to gauge the degree to which “early” visual processes such as spatial filtering and response normalization could account for human brightness percepts in a set of canonical stimuli including the White effect (44-46), classical simultaneous brightness contrast (SBC) (25), and grating induction (GI) (3, 5, 20, 34, 37, 48). The ODOG model successfully predicts changes in the magnitude of the White effect (9) and GI (11) as a function of inducing grating spatial frequency and test patch height, as well as the relative magnitude of brightness variations in many other stimuli including the Hermann Grid (8), the Gelb Staircase (16,17), the Wertheimer-Benary Cross (4, 7, 8), Howe's variations on White’s stimulus (15, 28), Todorovic’s (43) and Williams, McCoy, & Purves’ (47) variations on the SBC stimulus (6, 12), the checkerboard induction stimulus (9, 19), the shifted White stimulus (9, 45), Adelson’s Checker-Shadow (1, 12), Snake stimulus (2, 8, 12, 41), and Corrugated Mondrian stimuli (1, 8), including Todorovic’s variation (7, 8, 43), Hillis & Brainard’s Paint/Shadow stimulus (12, 27), “remote” induction stimuli (8, 10, 32, 40), and in the probe discs placed in Cartier-Bresson photographs (12, 22).
开发了面向高斯差分(ODOG)模型(6),以衡量“早期”视觉过程(如空间滤波和响应归一化)在一系列典型刺激下对人类亮度感知的影响程度,这些典型刺激包括White效应(44-46)、经典同步亮度对比(SBC)(25)和光栅感应(GI)(3,5,20,34,37,48)。ODOG模型成功预测变化的大小白色效果(9)和胃肠道(11)诱导光栅空间频率的函数和测试补丁的高度,以及亮度变化的相对大小在许多其他刺激包括赫尔曼网格(8),Gelb楼梯(16、17),Wertheimer-Benary交叉(4、7、8),豪的变化在白色的刺激(15,28),Todorovic(43)和威廉姆斯,真品,Purves的南方浸信会(47)变体刺激(6、12),棋盘感应刺激(9,19)、移位白色刺激(9,45)、Adelson的棋盘阴影刺激(1,12)、Snake刺激(2,8,12,41)和瓦状蒙德里安刺激(1,8),包括Todorovic的变异刺激(7,8,43)、Hillis & Brainard的油漆/阴影刺激(12,27)、“远程”感应刺激(8,10,32,40),以及放置在卡蒂埃-布列松照片中的探针盘(12,22)。
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引用次数: 5
Image processing applications through a variational perceptually-based color correction related to Retinex 图像处理应用程序通过一种基于变分感知的色彩校正与视网膜相关
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-317
Javier Vazquez-Corral, Syed Waqas Zamir, A. Galdran, David Pardo, Marcelo, Bertalmío
Comunicacio presentada al IS&T International Symposium on Electronic Imaging, celebrat del 14 al 18 de febrer de 2016 a San Francisco (CA, USA) i organitzat per la Society for Imaging Science and Technology.
Comunicacio presentada al IS&T International Symposium on Electronic Imaging, celebrat del 14 al 18 de febrer de 2016 a San Francisco (CA, USA) i organitzat per la Society for Imaging Science and Technology.
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引用次数: 5
A generalized white-patch model for fast color cast detection in natural images 自然图像快速偏色检测的广义白斑模型
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-318
J. Lisani, A. Petro, E. Provenzi, Catalina Sbert
We present a generalized white-patch technique able to rapidly detect color cast of natural images. Instead of relying on the chromatic information of a single perfectly reflective patch in the image, as pure white-patch models do, we consider a connected region of pixels that will serve as white reference for the method. The pixels belonging to the white reference region must comply with three properties: 1) they do not have to be completely saturated; 2) they must belong to the p% of pixels with brightest intensity in the whole image (where p is a parameter of the model); 3) the area of the connected region formed by these pix-els must overcome a threshold of significance A (a second parameter). Color cast is detected if the average intensity in the three separated chromatic channels RGB is distant enough from a neutral grey level, where the distance is measured through an angular metric.
提出了一种能够快速检测自然图像偏色的广义白斑技术。我们不像纯白斑模型那样依赖于图像中单个完美反射斑的颜色信息,而是考虑一个连接的像素区域,作为该方法的白色参考。属于白色参考区域的像素必须符合三个属性:1)它们不必完全饱和;2)它们必须属于整个图像中亮度最亮的像素的p%(其中p是模型的参数);3)这些像素构成的连通区域的面积必须超过显著性阈值a(第二个参数)。如果三个分离的颜色通道RGB中的平均强度距离中性灰度足够远,则检测到偏色,其中距离通过角度量来测量。
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引用次数: 1
Retinex Algorithms: Many spatial processes used to solve many different problems Retinex算法:用于解决许多不同问题的许多空间处理
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-017
J. McCann
There are many different Retinex algorithms. They make different assumptions, and attempt to solve different problems. They have different goals, ground truths and output results. This “Retinex at 50 Workshop” session compares the variety of Retinex algorithms, along with their goals, ground truths that measure the success of their results. All Retinex algorithms use spatial comparisons to calculate the appearances of the entire scene. All Retinex algorithms need observer data to quantify human vision, so as to evaluate their accuracy. The most critical component of all Retinex experiments is the observer matches used to characterize human spatial vision. This paper reviews the experiments that have evolved as a result of Retinex Theory. They provide a very challenging data set for algorithms that predict appearance. Introduction Edwin Land coined the word Retinex in 1963. He used it to describe the theoretical need for three independent color channels to explain human color constancy.[1] The word was a contraction of “retina” and “cortex”. A “Retinex” is a theoretical color channel that makes spatial comparisons so as to calculate lightness sensations, namely the range of appearances between light and dark. Land had enthusiastically experimented with two-color projections in the late 1950’s and early 60’s.[2] By that time, he had hundreds of patents on many different photographic systems. He was well aware of the possibilities, and limitations, of silver halide photography. Before his Red and White light projection experiments, he accepted the standard explanation of color. Namely, color was the result of the local quanta catches of receptors with different spectral sensitivities. Human color vision was thought to behave the way that color film did; in that color was a local phenomenon that resulted from spectral responses within each very small image segment. The quanta catches of the triplet of retinal cones in a small retinal region generated color appearances. An accidental observation made a colleague in a late-night experiment changed all. The colleague remarked that there was more color than expected from mixtures of photographic separations using red and white lights. Land responded: “ Oh yes, that is adaptation.” At two o’clock in the morning, Land sat up in bed, and said : “Adaptation, what adaptation?” He immediately returned to the lab to repeat the experiment. For the rest of his life, human color vision was a favorite research area. What was it that Land had seen, so briefly, that made him return to the lab in the middle of the night? Human Trichromatic Color Theory and film have always been linked. When Thomas Young made his famous suggestion of human trichromacy in 1802, his colleague at the Royal Institution, Humphrey Davy, was studying a black and white photographic system. Young was the editor of the Institutions journal that described the work.[3] Young was well aware of silver halide’s response to light. That night, Land rea
有许多不同的Retinex算法。他们做出不同的假设,试图解决不同的问题。他们有不同的目标、基本事实和输出结果。这个“Retinex 50周年研讨会”比较了各种Retinex算法,以及它们的目标,衡量它们结果成功的基本事实。所有的Retinex算法都使用空间比较来计算整个场景的外观。所有的Retinex算法都需要观测者的数据来量化人类视觉,从而评估其准确性。所有Retinex实验中最关键的组成部分是用于表征人类空间视觉的观察者匹配。本文综述了视网膜理论发展起来的实验。它们为预测外观的算法提供了非常具有挑战性的数据集。埃德温·兰德在1963年创造了“视网膜”这个词。他用它来描述理论需要三个独立的颜色通道来解释人类的颜色恒常性。[1]这个词是“视网膜”和“皮层”的缩写。“Retinex”是一种理论上的颜色通道,它通过空间比较来计算亮度感觉,即明暗之间的外观范围。在20世纪50年代末和60年代初,兰德曾热情地尝试过双色投影。[2]到那时,他在许多不同的摄影系统上拥有数百项专利。他很清楚卤化银摄影的可能性和局限性。在他的红光和白光投射实验之前,他接受了对颜色的标准解释。也就是说,颜色是具有不同光谱灵敏度的受体的局部量子捕获的结果。人类的色彩视觉被认为和彩色胶片的行为方式一样;这种颜色是一种局部现象,是由每个非常小的图像段内的光谱响应引起的。在一个小的视网膜区域中,视网膜锥的三联体的量子捕获产生了颜色的外观。一位同事在一次深夜实验中偶然的观察改变了一切。这位同事说,用红白光混合的摄影分色比预期的要多。兰德回答说:“哦,是的,这就是适应。”凌晨两点钟,土地从床上坐起来,说:“适应,什么适应?”他立即回到实验室重复实验。在他的余生中,人类的色彩视觉是他最喜欢的研究领域。兰德究竟看到了什么,那么短暂,让他在半夜里回到实验室?人类三色理论和电影一直是联系在一起的。1802年,当托马斯·杨(Thomas Young)提出人类三色视觉的著名观点时,他在英国皇家学会的同事汉弗莱·戴维(Humphrey Davy)正在研究一种黑白摄影系统。杨是描述这项研究的《机构》杂志的编辑。[3]杨很清楚卤化银对光的反应。那天晚上,兰德意识到,他无法用一种对本地反应灵敏的卤化银系统来制作电影,使其表现出那种视觉效果。这些投影中的颜色外观不能从微小局部区域的受体的量子捕获来理解。人类的颜色外观是根本不同的。控制色彩感觉的是空间比较。卤化银薄膜在非常小的区域使用量子捕获,其中包括所有光敏颗粒的一小部分。远处的物体无法影响胶片对每个微小片段的量子捕捉的反应。图1显示了人类的视觉通路,它始于位于视网膜锥体和杆状受体远端尖端的视觉色素(红色椭圆)。这些视觉色素的量子捕获引发了对光的光谱响应。受体只对视网膜上的图像做出第一反应。外观是沿整个视觉通路进行空间加工的结果。图1所示。视觉路径中空间比较的许多阶段的说明。John Dowling通过描述复杂的视网膜空间相互作用,极大地扩展了Hecht和Wald的工作。[4]Berson最近发现黑视素和光色素在神经节细胞中的空间调节作用。[5]1953年,Kuffler[6]和Barlow[7]发现视神经的神经节细胞进行空间比较。Hubel和Wiesel [8], DeValois[9]在皮层中发现了空间比较细胞。Semir Zeki[10]在V4皮质细胞中发现了颜色恒定细胞。在过去的80年里,人类视觉通路研究的主要主题是在视觉通路的每个阶段记录人类的空间机制。的水平。视觉是一个空间过程。1974年,兰德在他的《星期五晚上在皇家学会的演讲》中写道:“这篇演讲是关于一种普遍未被认识到的动物感官——比例意义。 这是理性的意义,它处理到达我们眼睛的辐射,以这样一种方式发现物体与落在它们身上的辐射有关的恒定特性。[11]图2展示了围绕“Lightness and Retinex”这篇文章的论文。使用参考文献[12]下载并提供论文链接。1971年土地和麦凯恩指定1983年土地1986年土地1970年麦肯,土地,Tatnall坡度•74amcanns .pdf•75savoymcancn .pdf•78cMcCann等。pdf•78a麦肯,pdf•78bSavoy.pdf•80McCannHall.pdf 1971年Horn 1976年麦肯,麦基,泰勒1977年土地科学美国2012年麦肯,帕拉曼,里兹1978年土地,皇家研究所1970年土地,法拉利,卡根,麦肯重置1968年土地。艾夫斯奖牌地址1968 Land, McCann 1980 Frankle, McCann 2001, Sobol, McCann HP相机1999,McCann Hubel色域Retinex 1972 Stockham空间滤波器米兰Retinex 1973 McCann 1999 McCann 2004 McCann Retinex @ 40
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引用次数: 8
A center-surround framework for spatial image processing 一种用于空间图像处理的中心环绕框架
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-020
Vassilios Vonikakis, Stefan Winkler
This paper presents a computational framework inspired by the center-surround antagonistic receptive fields of the human visual system. It demonstrates that, starting from the actual pixel value (center) and a low-pass estimation of the pixel’s neighborhood (surround) and using a mapping function inspired by the shunting inhibition mechanism, some widely used spatial image processing techniques can be implemented, including adaptive tone-mapping, local contrast enhancement, text binarization and local feature detection. As a result, it highlights the relations of these seemingly different applications with the early stages of the human visual system and draws insights about their characteristics. Introduction Center-surround antagonistic Receptive Fields (RFs) are abundant in the Human Visual System (HVS). They have been found in many areas, such as the retina, the Lateral Geniculate Nucleus, V1 or in higher visual areas. It seems that this is a typical strategy that the HVS employs for local signal comparisons, not only in vision but in other sensory areas as well. The RFs of center-surround cells comprise two separate concentric regions sampling the photoreceptor mosaic (namely the center and the surround) that act antagonistically on the final output of the cell. ON center-surround cells exhibit increased output with higher photoreceptor activity on their center and decreased output with increased activity on their surround. Conversely, for OFF center-surround cells, higher photoreceptor activity on the center has a negative impact on their output, whereas, increased photoreceptor activity on the surround increases their output. The size of the two regions defines the spatial frequency of sampling: smaller RF sizes sample finer details from the photoreceptor mosaic, while larger sizes encode coarser scales of the same signal. Center-surround cells are essentially a biological implementation of spatial filtering. Spatial filtering is a very broad term, encompassing any kind of filtering operations that depend on the local content of the signal and are not globally constant. Almost all existing image processing and computational photography techniques include some kind of spatial image processing. Modern denoising, local contrast enhancement, scale decomposition, exposure fusion, HDR tone mapping are some of them. Most of these methods have some common grounds with the basic computational models of the early stages of the HVS. However these similarities are not always so evident. In this paper, we start from the computational model of the first stages of HVS, developed by Grossberg [24], and we adapt it for image processing operations. Explicitly modeling HVS is out of the scope of this paper. We rather draw inspiration from it in order to address real-world imaging problems. More specifically, we define a framework, inspired by Grossberg’s theory, that describes center-surround signal interactions. We show that such a framework can give rise to
本文提出了一个受人类视觉系统的中心-环绕对抗性感受野启发的计算框架。研究表明,从实际像素值(中心)和像素邻域(环绕)的低通估计出发,利用受分流抑制机制启发的映射函数,可以实现一些广泛使用的空间图像处理技术,包括自适应色调映射、局部对比度增强、文本二值化和局部特征检测。因此,它突出了这些看似不同的应用与人类视觉系统早期阶段的关系,并得出了对其特征的见解。人类视觉系统(HVS)中存在丰富的中心-环绕对抗性感受野(RFs)。它们存在于许多区域,如视网膜、膝状外侧核、V1或更高的视觉区域。这似乎是HVS用于局部信号比较的典型策略,不仅在视觉方面,而且在其他感官领域也是如此。中心-环绕细胞的rf包括两个独立的同心圆区域,采样光感受器马赛克(即中心和环绕),它们对细胞的最终输出起拮抗作用。ON中心环绕细胞的输出随着中心感光细胞活性的增加而增加,而输出随着周围感光细胞活性的增加而减少。相反,对于OFF中心-环绕细胞,中心较高的光感受器活性会对其输出产生负面影响,而周围光感受器活性的增加则会增加其输出。两个区域的大小决定了采样的空间频率:较小的RF尺寸从光感受器马赛克中采样更精细的细节,而较大的RF尺寸编码相同信号的较粗尺度。中心环绕细胞本质上是空间滤波的生物实现。空间滤波是一个非常广泛的术语,包括依赖于信号的局部内容而不是全局恒定的任何类型的滤波操作。几乎所有现有的图像处理和计算摄影技术都包括某种形式的空间图像处理。现代去噪、局部对比度增强、尺度分解、曝光融合、HDR色调映射就是其中的一些方法。这些方法大多与HVS早期阶段的基本计算模型有一些共同点。然而,这些相似之处并不总是那么明显。在本文中,我们从Grossberg[24]开发的HVS第一阶段的计算模型开始,并将其应用于图像处理操作。对HVS进行显式建模超出了本文的研究范围。我们宁愿从中汲取灵感,以解决现实世界的成像问题。更具体地说,我们定义了一个框架,受格罗斯伯格理论的启发,描述了中心环绕信号的相互作用。我们表明,这样的框架可以产生现有的空间图像处理技术,因为它们中的许多都是它的特殊情况。这在图像处理和生物视觉模型之间提供了一个更统一的视图,突出了它们的共同点,并展示了其他可以开发的潜在应用。传统上,中心环绕rf被建模为高斯差分(DoG)[13]。这个线性算子本质上近似于拉普拉斯算子,通过减去两个不同西格玛的高斯算子,以同一位置为中心。DoG是许多计算机视觉和图像处理算法的核心,如边缘检测[12]、尺度空间构建[1]和局部特征检测器[11]。与DoG算子的线性响应相反,HVS的中心环绕单元在其输入方面表现出非线性响应。有趣的是,它们的非线性响应被认为有助于照明不变性和对比度增强[24]。根据标准视网膜模型[6,21],网格位置(i, j) ON-center - OFF-surround细胞的输出Vi j服从膜生理学方程为:dVi j (t) dt = gleak (Vrest−Vi j) +Ci j (Eex−Vi j) +Si j (Einh−Vi j)
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引用次数: 1
Retinex-like computations in human lightness perception and their possible realization in visual cortex 人眼亮度感知的类视黄醇计算及其在视觉皮层的可能实现
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-021
M. Rudd
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引用次数: 6
Connections between Retinex, neural models and variational methods 视网膜、神经模型和变分方法之间的联系
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-316
M. Bertalmío
Comunicacio presentada al IS&T International Symposium on Electronic Imaging, celebrat del 14 al 18 de febrer de 2016 a San Francisco (CA, USA) i organitzat per la Society for Imaging Science and Technology.
Comunicacio presentada al IS&T International Symposium on Electronic Imaging, celebrat del 14 al 18 de febrer de 2016 a San Francisco (CA, USA) i organitzat per la Society for Imaging Science and Technology.
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引用次数: 3
Statistical Aspects of Space Sampling in Retinex models Retinex模型中空间采样的统计方面
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-319
G. Gianini
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引用次数: 8
The Role of Lightness Perception in Determining the Perceived Contrast of Real World Scenes 明度感知在决定现实世界场景感知对比度中的作用
Pub Date : 2016-02-14 DOI: 10.2352/ISSN.2470-1173.2016.6.RETINEX-022
D. Kane, M. Bertalmío
Comunicacio presentada al IS&T International Symposium on Electronic Imaging, celebrat del 14 al 18 de febrer de 2016 a San Francisco (CA, USA) i organitzat per la Society for Imaging Science and Technology.
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引用次数: 1
期刊
Retinex at 50
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