Automatic Grayscale Image Colorization using a Deep Hybrid Model

K. Kiani; R. Hematpour; R. Rastgoo

Volume 9, Issue 3 , July 2021, , Pages 321-328

http://dx.doi.org/10.22044/jadm.2021.9957.2131

Abstract
  Image colorization is an interesting yet challenging task due to the descriptive nature of getting a natural-looking color image from any grayscale image. To tackle this challenge and also have a fully automatic procedure, we propose a Convolutional Neural Network (CNN)-based model to benefit from the ...  Read More

An Image Restoration Architecture using Abstract Features and Generative Models

A. Fakhari; K. Kiani

Volume 9, Issue 1 , January 2021, , Pages 129-139

http://dx.doi.org/10.22044/jadm.2020.9691.2101

Abstract
  Image restoration and its different variations are important topics in low-level image processing. One of the main challenges in image restoration is dependency of current methods to the corruption characteristics. In this paper, we have proposed an image restoration architecture that enables us to address ...  Read More

A Deep Model for Super-resolution Enhancement from a Single Image

N. Majidi; K. Kiani; R. Rastgoo

Volume 8, Issue 4 , November 2020, , Pages 451-460

http://dx.doi.org/10.22044/jadm.2020.9131.2052

Abstract
  This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model ...  Read More