Literature DB >> 18989034

An efficient naturalness-preserving image-recoloring method for dichromats.

Giovane R Kuhn1, Manuel M Oliveira, Leandro A F Fernandes.   

Abstract

We present an efficient and automatic image-recoloring technique for dichromats that highlights important visual details that would otherwise be unnoticed by these individuals. While previous techniques approach this problem by potentially changing all colors of the original image, causing their results to look unnatural to color vision deficients, our approach preserves, as much as possible, the image's original colors. Our approach is about three orders of magnitude faster than previous ones. The results of a paired-comparison evaluation carried out with fourteen color-vision deficients (CVDs) indicated the preference of our technique over the state-of-the-art automatic recoloring technique for dichromats. When considering information visualization examples, the subjects tend to prefer our results over the original images. An extension of our technique that exaggerates color contrast tends to be preferred when CVDs compared pairs of scientific visualization images. These results provide valuable information for guiding the design of visualizations for color-vision deficients.

Year:  2008        PMID: 18989034     DOI: 10.1109/TVCG.2008.112

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  3 in total

1.  FluoRender: An Application of 2D Image Space Methods for 3D and 4D Confocal Microscopy Data Visualization in Neurobiology Research.

Authors:  Yong Wan; Hideo Otsuna; Chi-Bin Chien; Charles Hansen
Journal:  IEEE Pac Vis Symp       Date:  2012

2.  A Survey of Colormaps in Visualization.

Authors:  Liang Zhou; Charles D Hansen
Journal:  IEEE Trans Vis Comput Graph       Date:  2015-10-26       Impact factor: 4.579

3.  A Novel Approach to Image Recoloring for Color Vision Deficiency.

Authors:  George E Tsekouras; Anastasios Rigos; Stamatis Chatzistamatis; John Tsimikas; Konstantinos Kotis; George Caridakis; Christos-Nikolaos Anagnostopoulos
Journal:  Sensors (Basel)       Date:  2021-04-13       Impact factor: 3.576

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.