Image enhancement via texture protection Retinex
Abstract Images obtained in dim light do not clearly represent the target scene, limiting information transmission on the image carrier. This study proposes a texture‐preserving image enhancement method, i.e. ETPR. The proposed method draws the illumination map of a low light image by Max‐RGB, and t...
Main Authors: | Linlu Dong, Liangjun Zhao, Jun Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | IET Image Processing |
Online Access: | https://doi.org/10.1049/ipr2.12311 |
Similar Items
-
Optimization algorithm for low‐light image enhancement based on Retinex theory
by: Jie Yang, et al.
Published: (2023-02-01) -
Retinex Based Image Enhancement via General Dictionary Convolutional Sparse Coding
by: Jongsu Yoon, et al.
Published: (2020-06-01) -
Low-Light Image Enhancement via Retinex-Style Decomposition of Denoised Deep Image Prior
by: Xianjie Gao, et al.
Published: (2022-07-01) -
Low-light Image Enhancement Based on Retinex Theory by Convolutional Neural Network
by: ZHAO Zheng-peng, LI Jun-gang, PU Yuan-yuan
Published: (2022-06-01) -
Multi-scale fusion framework via retinex and transmittance optimization for underwater image enhancement
by: Tie Li, et al.
Published: (2022-01-01)