Paper Image

Recursive decomposition of images into illumination components

Published on:

2 April 2024

Primary Category:

Computer Vision and Pattern Recognition

Paper Authors:

Saurabh Saini,

P J Narayanan


Key Details

Decomposes images into additive illumination components

Model-driven network with few parameters estimates components

Components enable targeted image enhancement regions

Improves state-of-the-art in low-light enhancement

Components beneficial for dehazing, deraining when combined with networks

AI generated summary

Recursive decomposition of images into illumination components

This paper presents a technique to decompose images into multiple illumination components in a recursive manner. A model-driven neural network is used to estimate these components, requiring only a small number of parameters. The components isolate regions with similar lighting characteristics, enabling targeted image enhancement. When applied to low-light image enhancement without paired training data, the method improves state-of-the-art performance. The illumination components also benefit other tasks like dehazing and deraining when combined with separate networks, demonstrating versatility.

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