Example-Based Color Transformation of Image and Video Using Basic Color Categories

Chang, Youngha; Saito, Suguru; Nakajima, M.

doi:10.1109/tip.2006.888347

Cited by 56 publications

(38 citation statements)

References 19 publications

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“…It restricts the color transfer to a specific color category according to a given color. To categorize the colors, the Basic Color Terms (BCTs), which are black, white, red, green, yellow, blue, brown, purple, pink, orange, and gray, are adopted [11], [12]. A color-naming segmentation experiment was conducted for color categorization.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Yet, since a global color transfer method based on pixelwise matching lacks spatial information, significant spatial Copyright c 2015 The Institute of Electronics, Information and Communication Engineers artifacts are produced, such as local color distortion and gradient differences. Thus, Chang proposed an example-based color transfer method, which transfers color using linear mapping based on a basic convex hull in each color category [11], [12]. However, the color transfer is restricted to individual color categories.…”

Section: Introductionmentioning

confidence: 99%

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Color Improvement Based on Local Color Transfer in Digital Intermediate of Digital Cinema

Kim

Kyung

et al. 2015

IEICE Trans. Inf. ^|^ Syst.

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SUMMARYIn digital cinema, an image goes through many types of processes like scanning, mastering, and digital intermediate. Among them, the digital intermediate process plays a central role because it determines the final color of an image. It edits and changes the colors of the images. However, some color distortions such as color bleeding are generated when editing and changing local colors in an image. In this paper, local color improvement for digital intermediate is proposed based on color transfer. Our method is simple and efficient color improvement that does not requires neither precise image segmentation nor feature matching. To prevent color distortions, a modified color influence map is proposed with color categories. First, the source image is roughly segmented using a color category map, which groups similar colors in color space. Second, the color influence map is modified by assigning different weights to the lightness and chroma components. Lastly, the modified color influence map and color category map filtered with anisotropic diffusion are combined. Experimental results show that the proposed method produces less color distortion in the resulting image.

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Section: The Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Color Improvement Based on Local Color Transfer in Digital Intermediate of Digital Cinema

Kim

Kyung

et al. 2015

IEICE Trans. Inf. ^|^ Syst.

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“…To categorize the colors, Basic Color Terms (BCTs) are adopted. The BCTs are black, white, red, green, yellow, blue, brown, purple, pink, orange, and gray [5] [6]. Color categorization of the target is shown in figure 5.…”

Section: B Proposed Methodsmentioning

confidence: 99%

Local color transfer using modified color influence map with color category

Kim

Jang

et al. 2011

2011 IEEE International Conference on Consumer Electronics -Berlin (ICCE-Berlin)

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Local color transfer is the process of assigning a given color to a local region in a target image. The local region that contains the given color has to be segmented. Conventionally, the segmentation of the corresponding local region in a target image is based on the color distance. The region which is the closest in color distance is separated. However, since the close range of color distance separating a given color from target image is ambiguous and uncertain, color distortion is often generated around a separated local region. Therefore, this paper addresses the problem of segmentation in a local color transfer. To prevent color distortion, a modified color influence map is proposed with color categories. First, the target image is roughly segmented using a color category map, which groups similar colors in color space. It restricts the color transfer to a specific color category according to a given color. Second, modified color influence map assigning different weight to lightness and chroma, respectively, is used instead of Euclidian color distance. Then, by combining a modified color influence map and color category map filtered with anisotropic diffusion, a local region that contains a given color can be segmented more strictly than conventional method. Experimental results show that the proposed method has less color distortion in the resulting image.

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“…By transferring means and standard deviations in backgrounds from reference view to current view, the corrected result for each frame in current view is described as [14] ref , y) is color value of current view in (x, y) and I i cour (x, y) is its corresponding corrected color value. From the mentioned above, the processing of proposed coding-oriented multi-view video color correction method as illustrated in Fig.2, which can be carried out by the following steps:…”

Section: Coding-oriented Multi-view Video Color Correction Methodsmentioning

confidence: 99%

Coding-oriented multi-view video color correction

Shao

Jiang

et al. 2008

J. Electron.(China)

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Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Group Of Pictures (GOP) by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results show the proposed method can obtain better performances in color correction and multi-view video coding.

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Example-Based Color Transformation of Image and Video Using Basic Color Categories

Cited by 56 publications

References 19 publications

Color Improvement Based on Local Color Transfer in Digital Intermediate of Digital Cinema

Color Improvement Based on Local Color Transfer in Digital Intermediate of Digital Cinema

Local color transfer using modified color influence map with color category

Coding-oriented multi-view video color correction

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