Image analogies is a framework for processing images by example. Image analogies uses training data A and A′ in order to learn a filter that can be applied to an unfiltered target image B to produce an analogous image B′. This means that B′ relates to B the same way A′ relates to A. The framework is general and can be applied to many different applications. Typical applications for image analog...

This paper proposes a colorization algorithm for infrared images based on Conditional Generative Adversarial Network (CGAN) with multi-scale feature fusion and attention mechanisms, aiming to address issues such as color leakage unclear semantics in existing image coloring methods. Firstly, we improved the generator of CGAN network by incorporating extraction module into U-Net architecture fuse...

Quantum dot color conversion as a display form, it can greatly improve the gamut of OLED, and also be used an effective colorization technology solution for MicroLED. Here we design quantum pixel structure, carry out preparation verification big‐thickness BM, Bragg reflector prepare devices initially. After evaluation, give corresponding suggestions application research later conversion.

Color assignment is a complex task of incorporating and balancing area configuration, color harmony, and user’s intent. In this paper, we present a novel method for automatic color assignment based on theories of color perception. We define color assignment as an optimization problem with respect to the color relationships as well as the spatial configuration of input segments. We also suggest ...

We propose a principled convolutional neural pyramid (CNP) framework for general low-level vision and image processing tasks. It is based on the essential finding that many applications require large receptive fields for structure understanding. But corresponding neural networks for regression either stack many layers or apply large kernels to achieve it, which is computationally very costly. O...