CVIVJan 31, 2021

Tone Mapping Based on Multi-scale Histogram Synthesis

arXiv:2102.00408v13 citationsHas Code
Originality Incremental advance
AI Analysis

This addresses the display limitation for users of low dynamic range devices, but it is incremental as it builds on existing tone mapping approaches.

The paper tackles the problem of displaying wide dynamic range images on low dynamic range devices by proposing a tone mapping algorithm based on multi-scale histogram synthesis, which generates high brightness, good contrast, and appealing images that surpass many state-of-the-art methods.

In this paper, we present a novel tone mapping algorithm that can be used for displaying wide dynamic range (WDR) images on low dynamic range (LDR) devices. The proposed algorithm is mainly motivated by the logarithmic response and local adaptation features of the human visual system (HVS). HVS perceives luminance differently when under different adaptation levels, and therefore our algorithm uses functions built upon different scales to tone map pixels to different values. Functions of large scales are used to maintain image brightness consistency and functions of small scales are used to preserve local detail and contrast. An efficient method using local variance has been proposed to fuse the values of different scales and to remove artifacts. The algorithm utilizes integral images and integral histograms to reduce computation complexity and processing time. Experimental results show that the proposed algorithm can generate high brightness, good contrast, and appealing images that surpass the performance of many state-of-the-art tone mapping algorithms. This project is available at https://github.com/jieyang1987/ToneMapping-Based-on-Multi-scale-Histogram-Synthesis.

Code Implementations1 repo
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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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