Color Enhancement of Low Illumination Garden Landscape Images
Author:
Zhang Qian,Lu Shuang,Liu Lei,Liu Yi,Zhang Jing,Shi Daoyuan
Abstract
The unfavorable shooting environment severely hinders the acquisition of actual landscape information in garden landscape design. Low quality, low illumination garden landscape images (GLIs) can be enhanced through advanced digital image processing. However, the current color enhancement models have poor applicability. When the environment changes, these models are easy to lose image details, and perform with a low robustness. Therefore, this paper tries to enhance the color of low illumination GLIs. Specifically, the color restoration of GLIs was realized based on modified dynamic threshold. After color correction, the low illumination GLI were restored and enhanced by a self-designed convolutional neural network (CNN). In this way, the authors achieved ideal effects of color restoration and clarity enhancement, while solving the difficulty of manual feature design in landscape design renderings. Finally, experiments were carried out to verify the feasibility and effectiveness of the proposed image color enhancement approach.
Funder
2021 Philosophy and Social Science planning project of Henan Province
2021 Philosophy and Social Science project of Henan Province
Special Application for Key Research and Development and Promotion of Henan Province
Research on Strategies for Memory Protection and Inheritance of Industrial and Trade Traditional Villages in Henan from the Perspective of Village Culture
Research on Spatial Satisfaction Evaluation and Renewal Protection Strategy for Inheritance of Traditional Village Context in Southern Henan province
Subject of Henan Social Science Planning
Research on Spatial Feature Improvement design of Traditional Village Landscape in Southern Henan Under Protection Early Warning Strategy
Publisher
International Information and Engineering Technology Association
Subject
Electrical and Electronic Engineering