automaticgrayscaleimagecolorization

由 R Sarapu 著作 · 2021 · 被引用 1 次 — In[11], a fully automated grayscale image colorization method based on neural networks and optimization was proposed. It separates grayscale pigments into ...

Colorization of grayscale images is a simple task for the human imagination. Researchers from the Toyota Technological Institute at Chicago and University ...

由 A Sousa 著作 · 被引用 17 次 — Subsequently, colorizing a grayscale image consists of (a) extracting the same set of features from each pixel, (b) estimating the probability for each color at ...

由 J Fan 著作 · 被引用 1 次 — [25] used conditional generative adversarial networks (cGANs) to color grayscale images without requiring users to interactively fine-tune the coloring results.

由 S Liu 著作 · 2012 · 被引用 54 次 — Colorization aims to adding colors to a grayscale image. This task is ill-posed in the sense that assigning the colors to a grayscale image ...

We learn to automatically color grayscale images with a deep network. Our network learns both local features and global features jointly in a single framework.

由 I Žeger 著作 · 2021 · 被引用 43 次 — Colorization is a process of converting grayscale images into visually acceptable color images. The main goal is to convince the viewer of ...

由 C Liang 著作 · 2024 — Automatic colorization of grayscale image has been a challenging task. Previous research have applied supervised methods in conquering this ...

The grayscale images represent only the intensity information of the light from the darkest black to the brightest white and which can later be colorized. But ...