Quality Assessment of Natural Landscape Images Colorization based on Neural Network Autoencoder
Abstract
Quality Assessment of Natural Landscape Images Colorization based on Neural Network Autoencoder
Incoming article date: 11.05.2024The article discusses the application of neural network autoencoder in the problem of monochrome image colorization. The description of the network architecture, the applied training method and the method of preparing training and validation data is given. A dataset consisting of 540 natural landscape images with a resolution of 256 by 256 pixels was used for training. The results of comparing the quality of the outputs of the obtained model were evaluated and the average coefficients of metrics as well as the mean squared error of the VGG model outputs are presented.
Keywords: neural networks, machine learning, autoencoder, image quality analysis, colorization, CIELAB