Multi Scale Tone Mapping Model Using Visual Brightness Functions for HDR Image Compression 


Vol. 37,  No. 12, pp. 1054-1064, Dec.  2012


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  Abstract

HDR (high dynamic range) tone mapping algorithms are used in image processing that reduces the dynamic range of an image to be displayed on LDR (low dynamic range) devices properly. The retinex is one of the tone mapping algorithms to provide dynamic range compression, color constancy, and color rendition. It has been developed through multi-scale methods and luminance-based methods. Retinex algorithms still have drawbacks such as the emphasized noise and desaturation. In this paper, we propose a multi scale tone mapping algorithm for enhancement of contrast, saturation, and noise of HDR rendered images based on visual brightness functions. In the proposed algorithm, HSV color space has been used for preserving the hue and saturation of images. And the algorithm includes the estimation of minimum and maximum luminance level and a visual gamma function for the variation of viewing conditions. And subjective and objective evaluations show that proposed algorithm is better than existing algorithms. The proposed algorithm is expected to image quality enhancement in some fields that require a improvement of the dynamic range due to the changes in the viewing condition.

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  Cite this article

[IEEE Style]

H. Kwon, S. Lee, S. Chae, K. Sohng, "Multi Scale Tone Mapping Model Using Visual Brightness Functions for HDR Image Compression," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 12, pp. 1054-1064, 2012. DOI: .

[ACM Style]

Hyuk-ju Kwon, Sung-hak Lee, Seok-min Chae, and Kyu-ik Sohng. 2012. Multi Scale Tone Mapping Model Using Visual Brightness Functions for HDR Image Compression. The Journal of Korean Institute of Communications and Information Sciences, 37, 12, (2012), 1054-1064. DOI: .

[KICS Style]

Hyuk-ju Kwon, Sung-hak Lee, Seok-min Chae, Kyu-ik Sohng, "Multi Scale Tone Mapping Model Using Visual Brightness Functions for HDR Image Compression," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 12, pp. 1054-1064, 12. 2012.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880