Color Constancy

Key Words : faded image enhancement, gray world algorithm, multi-scale process ABSTRACT Fading effect of old pictures and printings is shown up differently according to the ink property, temperature, humidity, illuminants, and so on. Faded image enhancement techniques based on illuminant estimation are proposed such as the gray world algorithm and white patch retinex methods. However, conventional simple operators are not suitable for enhancing faded images because partial fading effect is appeared differently. Thus, this paper presents a color enhancement algorithm based on integrating correction coefficients for faded images.First, the proposed method adopts local process by using multi-scale average mask. The coefficients for each multi-scale average mask are obtained to apply the gray world algorithm. Then, integrating the coefficients with weights is performed to calculate correction ratio for red and blue channels in the gray world assumption.Finally, the enhanced image is obtained by applying the integrated coefficients to the gray world algorithm. In the experimental results, the proposed method reproduces better colors for both wholly and partially faded images compared with the previous methods.

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Section: 한편 색 바랜 영상의 보정을 위하여 칼라 항상성unclassified

Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm

Kyung

Kim

2014

The Journal of Korea Information and Communications Society

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“…If the illumination is constant, the influence of the illumination can be removed by computing the first derivative [4]. This works if the two neighboring pixels have the same illumination.…”

Section: Local Illumination and Reflectance Estimationmentioning

confidence: 99%

“…Yet, such contrast corrections are limited because the sensitivity of the human eye changes locally according to the position of an object and the illumination in the scene. Therefore a spatial adaptive method is needed to overcome these limitations [4], and it has led to the development of the center/surround retinex model [5], [6], and multi-scale retinex (MSR) [7], [8].…”

Section: Introductionmentioning

confidence: 99%

A Contrast Enhancement Method for HDR Image Using a Modified Image Formation Model

Yun

Hong

Choi

2012

IEICE Trans. Inf. & Syst.

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SUMMARYPoor illumination and viewing conditions have negativeinfluences on the quality of an image, especially the contrast of the dark and bright region. Thus, captured and displayed images usually need contrast enhancement. Histogram-based or gamma correction-based methods are generally utilized for this. However, these methods are global contrast enhancement method, and since the sensitivity of the human eye changes locally according to the position of the object and the illumination in the scene, the global contrast enhancement methods have a limit. The spatial adaptive method is needed to overcome these limitations and it has led to the development of an integrated surround retinex (ISR), and estimation of dominant chromaticity (EDC) methods. However, these methods are based on Gray-World Assumption, and they use a general image formation model, so the color constancy is known to get poor results, shown through graying-out, halo-artifacts (ringing effects), and the dominated color. This paper presents a contrast enhancement method using a modified image formation model in which the image is divided into three components: global illumination, local illumination and reflectance. After applying the power constant value to control the contrast in the resulting image, the output image is obtained from their product to avoid or minimize a color distortion, based on the sRGB color representation. The experimental results show that the proposed method yields better performances than conventional methods. key words: modified image formation model, global illumination, local illumination, reflectance, JND-based adaptive smoothing method

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“…This large variation in intensity (10 9 [1]) of an illuminant makes the performance of the state of the art colour constancy algorithms to degrade in HDR scenes [2]. Recent research shows that the most advanced algorithms are not able to provide stable chromaticity that can be used in colour based recognition applications [3].…”

Section: Introductionmentioning

confidence: 99%

Optimum Sensors for ‘Chromaticity’ Constancy in the Pixel

Ratnasingam

Collins

2009

Image Analysis and Processing – ICIAP 2009

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Abstract. In machine vision systems recording the colour of an object is crucial for applications such as skin detection while it will enhance applications including colour based recognition and image retrieval. Unfortunately, almost none of the existing colour constancy algorithms have been designed to deal with the high dynamic ranges that can occur in external, naturally illuminated scenes. One algorithm that can deal with these scenes has been proposed by Finlayson and Drew. In this paper a method of assessing the performance of this algorithm, and equivalent algorithms, are proposed. The performance of this algorithm is then significantly improved by optimising the spectral response of the sensors used to obtain the data required by algorithm. Since the resulting performance is comparable to that of the human visual system it appears that this algorithm is capable of obtaining useful chromaticity information under highly varying illumination conditions.

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Color Constancy

Cited by 160 publications

References 0 publications

Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm

Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm

A Contrast Enhancement Method for HDR Image Using a Modified Image Formation Model

Optimum Sensors for ‘Chromaticity’ Constancy in the Pixel

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