APSIPA Transactions on Signal and Information Processing > Vol 3 > Issue 1

A fixed-point implementation of tone mapping operation for HDR images expressed in floating-point format

Toshiyuki Dobashi, Tokyo Metropolitan University, Japan, Atsushi Tashiro, Tokyo Metropolitan University, Japan, Masahiro Iwahashi, Nagaoka University of Technology, Japan, Hitoshi Kiya, Tokyo Metropolitan University, Japan, kiya@tmu.ac.jp
 
Suggested Citation
Toshiyuki Dobashi, Atsushi Tashiro, Masahiro Iwahashi and Hitoshi Kiya (2014), "A fixed-point implementation of tone mapping operation for HDR images expressed in floating-point format", APSIPA Transactions on Signal and Information Processing: Vol. 3: No. 1, e10. http://dx.doi.org/10.1017/ATSIP.2014.9

Publication Date: 08 Oct 2014
© 2014 Toshiyuki Dobashi, Atsushi Tashiro, Masahiro Iwahashi and Hitoshi Kiya
 
Subjects
 
Keywords
HDRTone mappingLow-memoryFixed-pointFloating-point
 

Share

Open Access

This is published under the terms of the Creative Commons Attribution licence.

Downloaded: 758 times

In this article:
I. INTRODUCTION 
II. PRELIMINARIES 
III. PROPOSED METHOD 
IV. EXPERIMENTAL AND EVALUATION RESULTS 
V. CONCLUSION 

Abstract

A tone mapping operation (TMO) for HDR images with fixed-point arithmetic is proposed. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image by compressing its dynamic range. Since HDR images are generally expressed in a floating-point data format, a TMO also deals with floating-point data even though resulting LDR images have integer data. As a result, conventional TMOs require many resources such as computational and memory cost. To reduce the resources, an integer TMO which treats a floating-point number as two 8-bit integer numbers was proposed. However, this method has the limitation of available input HDR image formats. The proposed method introduces an intermediate format to relieve the limitation of input formats, and expands the integer TMO for the intermediate format. The proposed integer TMO can be applied for multiple formats such as the RGBE and the OpenEXR. Moreover, the method can conduct all calculations in the TMO with fixed-point arithmetic. Using both integer data and fixed-point arithmetic, the method reduces not only the memory cost, but also the computational cost. The experimental and evaluation results show that the proposed method reduces the computational and memory cost, and gives almost same quality of LDR images, compared with the conventional method with floating-point arithmetic.

DOI:10.1017/ATSIP.2014.9