3 citations · 3 across the 1 of their papers we have counts for
3 papers
eess.IV2021★ 3 cited
NLHD: A Pixel-Level Non-Local Retinex Model for Low-Light Image Enhancement
Hao Hou, Yingkun Hou, Yuxuan Shi +2
Retinex model has been applied to low-light image enhancement in many existing methods. More appropriate decomposition of a low-light image can help achieve better image enhancemen…
cs.CV2019
NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising
Yingkun Hou, Jun Xu, Mingxia Liu +4
Non-local self similarity (NSS) is a powerful prior of natural images for image denoising. Most of existing denoising methods employ similar patches, which is a patch-level NSS pri…
cs.CV2019
STAR: A Structure and Texture Aware Retinex Model
Jun Xu, Yingkun Hou, Dongwei Ren +5
Retinex theory is developed mainly to decompose an image into the illumination and reflectance components by analyzing local image derivatives. In this theory, larger derivatives a…