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arXiv · 2501.06448

Discovering an Image-Adaptive Coordinate System for Photography Processing

Ziteng Cui·Lin Gu·Tatsuya Harada
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Abstract

Curve & Lookup Table (LUT) based methods directly map a pixel to the target output, making them highly efficient tools for real-time photography processing. However, due to extreme memory complexity to learn full RGB space mapping, existing methods either sample a discretized 3D lattice to build a 3D LUT or decompose into three separate curves (1D LUTs) on the RGB channels. Here, we propose a novel algorithm, IAC, to learn an image-adaptive Cartesian coordinate system in the RGB color space before performing curve operations. This end-to-end trainable approach enables us to efficiently adjust images with a jointly learned image-adaptive coordinate system and curves. Experimental results demonstrate that this simple strategy achieves state-of-the-art (SOTA) performance in various photography processing tasks, including photo retouching, exposure correction, and white-balance editing, while also maintaining a lightweight design and fast inference speed.

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Ziteng Cui, Lin Gu, Tatsuya Harada. 2025-01-11. Discovering an Image-Adaptive Coordinate System for Photography Processing. https://arxiv.org/abs/2501.06448

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