# Spectral reflectance estimation from one RGB image using self-interreflections in a concave object

arXiv: https://arxiv.org/abs/1803.01595 · HTML: https://mlsanity.com/paper/1803.01595/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2018.

## Built on by (most cited first, 1 of 1)

- [Learning to Recover Spectral Reflectance from RGB Images](https://mlsanity.com/paper/2304.02162/) (2023)

## Abstract (arXiv)

Light interreflections occurring in a concave object generate a color gradient which is characteristic of the object's spectral reflectance. In this paper, we use this property in order to estimate the spectral reflectance of matte, uniformly colored, V-shaped surfaces from a single RGB image taken under directional lighting. First, simulations show that using one image of the concave object is equivalent to, and can even outperform, the state of the art approaches based on three images taken under three lightings with different colors. Experiments on real images of folded papers were performed under unmeasured direct sunlight. The results show that our interreflection-based approach outperforms existing approaches even when the latter are improved by a calibration step. The mathematical solution for the interreflection equation and the effect of surface parameters on the performance of the method are also discussed in this paper.