Literature DB >> 16671293

Fast image and video colorization using chrominance blending.

Liron Yatziv1, Guillermo Sapiro.   

Abstract

Colorization, the task of coloring a grayscale image or video, involves assigning from the single dimension of intensity or luminance a quantity that varies in three dimensions, such as red, green, and blue channels. Mapping between intensity and color is, therefore, not unique, and colorization is ambiguous in nature and requires some amount of human interaction or external information. A computationally simple, yet effective, approach of colorization is presented in this paper. The method is fast and it can be conveniently used "on the fly," permitting the user to interactively get the desired results promptly after providing a reduced set of chrominance scribbles. Based on the concepts of luminance-weighted chrominance blending and fast intrinsic distance computations, high-quality colorization results for still images and video are obtained at a fraction of the complexity and computational cost of previously reported techniques. Possible extensions of the algorithm introduced here included the capability of changing the colors of an existing color image or video, as well as changing the underlying luminance, and many other special effects demonstrated here.

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Mesh:

Year:  2006        PMID: 16671293     DOI: 10.1109/tip.2005.864231

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  3 in total

1.  Colour-reproduction algorithm for transmitting variable video frames and its application to capsule endoscopy.

Authors:  Tareq Khan; Ravi Shrestha; Md Shamin Imtiaz; Khan A Wahid
Journal:  Healthc Technol Lett       Date:  2015-02-05

2.  Artifact removal and texture-based rendering for visualization of 3D fetal ultrasound images.

Authors:  Shyh-Roei Wang; Yung-Nien Sun; Fong-Ming Chang
Journal:  Med Biol Eng Comput       Date:  2007-12-18       Impact factor: 2.602

3.  Wide-field computational color imaging using pixel super-resolved on-chip microscopy.

Authors:  Alon Greenbaum; Alborz Feizi; Najva Akbari; Aydogan Ozcan
Journal:  Opt Express       Date:  2013-05-20       Impact factor: 3.894

  3 in total

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