Semantic Scholar Open Access 2017 2539 sitasi

LIME: Low-Light Image Enhancement via Illumination Map Estimation

Xiaojie Guo Yu Li Haibin Ling

Abstrak

When one captures images in low-light conditions, the images often suffer from low visibility. Besides degrading the visual aesthetics of images, this poor quality may also significantly degenerate the performance of many computer vision and multimedia algorithms that are primarily designed for high-quality inputs. In this paper, we propose a simple yet effective low-light image enhancement (LIME) method. More concretely, the illumination of each pixel is first estimated individually by finding the maximum value in R, G, and B channels. Furthermore, we refine the initial illumination map by imposing a structure prior on it, as the final illumination map. Having the well-constructed illumination map, the enhancement can be achieved accordingly. Experiments on a number of challenging low-light images are present to reveal the efficacy of our LIME and show its superiority over several state-of-the-arts in terms of enhancement quality and efficiency.

Penulis (3)

X

Xiaojie Guo

Y

Yu Li

H

Haibin Ling

Format Sitasi

Guo, X., Li, Y., Ling, H. (2017). LIME: Low-Light Image Enhancement via Illumination Map Estimation. https://doi.org/10.1109/TIP.2016.2639450

Akses Cepat

Lihat di Sumber doi.org/10.1109/TIP.2016.2639450
Informasi Jurnal
Tahun Terbit
2017
Bahasa
en
Total Sitasi
2539×
Sumber Database
Semantic Scholar
DOI
10.1109/TIP.2016.2639450
Akses
Open Access ✓