Scene-Segmentation-Based Exposure Compensation for Tone Mapping of High Dynamic Range Scenes

We propose a novel scene-segmentation-based exposure compensation method for multi-exposure image fusion (MEF) based tone mapping. The aim of MEF-based tone mapping is to display high dynamic range (HDR) images on devices with limited dynamic range. To achieve this, this method generates a stack of differently exposed images from an input HDR image and fuses them into a single image. Our approach addresses the limitations of MEF-based tone mapping with existing segmentation-based exposure compensation, which often result in visually unappealing outcomes due to inappropriate exposure value selection. The proposed exposure compensation method first segments the input HDR image into subregions based on luminance values of pixels. It then determines exposure values for multi-exposure images to maximize contrast between regions while preserving relative luminance relationships. This approach contrasts with conventional methods that may invert luminance relationships or compromise contrast between regions. Additionally, we present an improved technique for calculating fusion weights to better reflect the effects of exposure compensation in the final fused image. In a simulation experiment to evaluate the quality of tone-mapped images, the MEF-based tone mapping with the proposed method outperforms three typical tone mapping methods including conventional MEF-based one, in terms of the tone mapped image quality index (TMQI).

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Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1109/apsipaasc63619.2025.10849135
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Scene-Segmentation-Based Exposure Compensation for Tone Mapping of High Dynamic Range Scenes

Hitoshi Kiya, Yuma Kinoshita
Industrial Vision Systems and Defect Detection
article

Scene-Segmentation-Based Exposure Compensation for Tone Mapping of High Dynamic Range Scenes

Hitoshi Kiya, Yuma Kinoshita
article en

Abstract

We propose a novel scene-segmentation-based exposure compensation method for multi-exposure image fusion (MEF) based tone mapping. The aim of MEF-based tone mapping is to display high dynamic range (HDR) images on devices with limited dynamic range. To achieve this, this method generates a stack of differently exposed images from an input HDR image and fuses them into a single image. Our approach addresses the limitations of MEF-based tone mapping with existing segmentation-based exposure compensation, which often result in visually unappealing outcomes due to inappropriate exposure value selection. The proposed exposure compensation method first segments the input HDR image into subregions based on luminance values of pixels. It then determines exposure values for multi-exposure images to maximize contrast between regions while preserving relative luminance relationships. This approach contrasts with conventional methods that may invert luminance relationships or compromise contrast between regions. Additionally, we present an improved technique for calculating fusion weights to better reflect the effects of exposure compensation in the final fused image. In a simulation experiment to evaluate the quality of tone-mapped images, the MEF-based tone mapping with the proposed method outperforms three typical tone mapping methods including conventional MEF-based one, in terms of the tone mapped image quality index (TMQI).

Tokai University (JP), Tokyo Metropolitan University (JP)
Openalex Percentile: Top 61%
Industrial Vision Systems and Defect Detection
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