Abstract
To solve the problem of missing or distorted detail texture when manually adjusting image parameters, a weak illumination image enhancement algorithm based on cyclic generation game network is proposed. The image features are normalized by Gaussian distribution. Combined with homomorphic filtering theory and defogging operation, the image is generated and denoised according to the network brightness to enhance the weak illumination image. The experimental results show that after using this method to process the image, the image entropy increases by 6.8%, the contrast increases by 27.5%, and the noise content decreases by 24.1%. It has better contrast. It can not only meet the enhancement effect of weak light, but also ensure the details of the image, so that the image has richer details and good visual appearance.
Subject
Computational Mathematics,Computer Science Applications,General Engineering
Reference16 articles.
1. Near-infrared hyperspectral imaging technology combined with deep convolutional generative adversarial network to predict oil content of single maize kernel;Liu;Food Chem.,2021
2. The national health information technology human factors and ergonomics agenda;Zayas-Cabán;Appl Ergonomics.,2020
3. Adaptive and dynamic ordering of illumination patterns with an image dictionary in single-pixel imaging;Yuan;Opt Commun.,2020
4. Implementation of a point spread function method to analyze flash radiography images: image enhancement, movie generation, and projection detangling;Zellner;Rev Sci Instrum.,2020
5. Comprehensive underwater object tracking benchmark dataset and underwater image enhancement with Gan;Panetta;IEEE J Oceanic Eng.,2021