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

TL;DR

This paper introduces a scene-segmentation-based exposure compensation technique for multi-exposure image fusion, enhancing tone mapping of HDR images by improving contrast and luminance preservation, resulting in higher quality images.

Contribution

It presents a novel segmentation-based exposure compensation method that optimizes contrast and luminance relationships for better HDR tone mapping.

Findings

Outperforms conventional methods in tone mapped image quality index (TMQI)

Enhances contrast preservation across segmented regions

Improves luminance relationship maintenance in fused images

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).