Corruptive Artifacts Suppression for Example-Based Color Transfer

Su, Zhuo; Zeng, Kun; Liu, Li; Li, Bo; Luo, Xiangfeng

doi:10.1109/tmm.2014.2305914

Cited by 43 publications

(34 citation statements)

References 37 publications

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“…The transferred output and the extracted multi-levels details are integrated by the measurement minimization to yield the final result. Our framework achieves a sound grain suppression, color fidelity and detail appearance seamlessly [1].…”

Section: Literature Surveymentioning

confidence: 99%

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A Colorization Algorithm with Artifacts Suppression on Real Time Video

2016

IJSR

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color manipulation is a very common activity in now a day. Color transfers between images are difficult operation in images editing but easily suffers from some corruptive artifacts in the mapping process. In this paper, a color transfer approach with corruptive artifacts suppression is represent, which performs iterative probabilistic color mapping and this Paper extend the technique to colorize the videos. It is done with the help of self-learning filtering scheme and multiscale detail manipulation scheme, which minimizes Kullback-Leibler distance. This will help us to colorize both already colored and gray scale videos. This method achieves a sound grain suppression which means it prevent from being published then a color fidelity that means the degree of exactness with which something is copied or reproduced and detail appearance. First, an iterative probabilistic color mapping is applied to construct the mapping relationship between the reference and target frames. Then, a self learning filtering scheme is applied into the transfer process to prevent from artifacts and extract details. The transferred output and the extracted multi-levels details are integrated. This is done by the measurement minimization to yield the final result.

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Section: Literature Surveymentioning

confidence: 99%

“…1. Example-based color transfer [1] is an image manipulation technique, but it would produce some unexpected artifacts due the intensity of images.…”

Section: Introductionmentioning

confidence: 99%

A Colorization Algorithm with Artifacts Suppression on Real Time Video

2016

IJSR

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“…They borrow the idea from example-based image color transfer [8,[13][14][15][16][17][18][19][20], which takes the color distribution of another image as reference. Specifically, they calculated the color statistics of gradient meshes and the example image, and adopted a PCA-based color transfer to update the color and local color gradients of mesh points.…”

Section: Related Workmentioning

confidence: 99%

Scribble-based gradient mesh recoloring

Wan

Xiao

Dou

et al. 2017

Multimed Tools Appl

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Previous gradient mesh recoloring methods usually have dependencies on an additional reference image and the rasterized gradient mesh. To circumvent such dependencies, we propose a user scribble-based recoloring method, in which users are allowed to annotate gradient meshes with a few color scribbles. Our approach builds an auxiliary mesh from gradient meshes, namely control net, by taking both colors and local color gradients at mesh points into account. We then develop an extended chrominance blending method to propagate the user specified colors over the control net. The recolored gradient mesh is finally reconstructed from the recolored control net. Experiments validate the effectiveness of our approach on multiple gradient meshes. Compared with various alternative solutions, our method has no color bleedings nor sampling artifacts, and can achieve fast performance.

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“…Because the CSS modification of color is don cation for Web Page Based on Partitional Color Transfer rain effect is a phenomenon appears due to enhancing nder the stretched mapping. Commonly, it looks like so [15]. The grain effect influences the user experience xt or making image unclear.…”

Section: Color Modificatmentioning

confidence: 99%

Automatic Color Modification for Web Page Based on Partitional Color Transfer

Chen¹,

Long²,

Luo³

2014

Lecture Notes in Computer Science

Self Cite

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Abstract. Designing or modifying the color of a website is a time-consuming and difficult task for most software engineers. The idea of this paper is inspired by the color transfer methods proposed for automatically alter an image's color during image processing. The color of a web page can be modified by reusing color characteristic of a reference page. However, a web page cannot be simply viewed as an image because it has structure and constraints for color modifying. In this paper, we propose an approach for automatic color modification of web page based on partitional color transfer. Our approach starts from the clustering of visible UI elements for page partition. And then, elements in the source page are color transferred with their matched elements in the reference page. Our approach automatically modifies the color of web pages based on the color transfer result. We generate 72 modified web pages to evaluate the page structure preserving and color characteristic transformation result of our approach.

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Corruptive Artifacts Suppression for Example-Based Color Transfer

Cited by 43 publications

References 37 publications

A Colorization Algorithm with Artifacts Suppression on Real Time Video

A Colorization Algorithm with Artifacts Suppression on Real Time Video

Scribble-based gradient mesh recoloring

Automatic Color Modification for Web Page Based on Partitional Color Transfer

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