Deep neural network joint multi-scale attention for remote sensing image colorization

Wang Yun; Jiang Qian; Jin Xin; Lee Shin-Jye; Jianan Feng; Ding Zhou; Ya Zhang

doi:10.1117/12.2599849

30 June 2021 Deep neural network joint multi-scale attention for remote sensing image colorization

Wang Yun, Jiang Qian, Jin Xin, Lee Shin-Jye, Jianan Feng, Ding Zhou, Ya Zhang

Proceedings Volume 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021); 118781P (2021) https://doi.org/10.1117/12.2599849
Event: Thirteenth International Conference on Digital Image Processing, 2021, Singapore, Singapore

Abstract

Image colorization is a technology to transform gray-scale image into natural color image, which is always a challenging task in image processing. In this paper, we design a deep neural network model including multi-scale convolutional down-sampling and attention mechanism, which can effectively solve the problem of coloring gray remote sensing image. First, we input the grayscale remote sensing image into the feature extractor of our model for feature extraction and multi-scale down-sampling. Second, the feature map extracted by the feature extractor is input into the squeeze-andexcitation attention mechanism module to enhance the extraction of key information. Finally, the feature map output by the feature extractor and squeeze-and-excitation module is input into the feature reconstructor for feature reconstruction and color restoration, and then color remote sensing images are obtained. Unlike the conventional methods, our method is an end-to-end model, and without any human interaction in the coloring process. The experimental results show that the color remote sensing image generated by our method is superior to the existing methods in both subjective and objective metrics.

Citation Download Citation

Wang Yun, Jiang Qian, Jin Xin, Lee Shin-Jye, Jianan Feng, Ding Zhou, and Ya Zhang "Deep neural network joint multi-scale attention for remote sensing image colorization", Proc. SPIE 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 118781P (30 June 2021); https://doi.org/10.1117/12.2599849

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Remote sensing

Convolution

Feature extraction

Image quality

Data modeling

Image processing

Neural networks

Show All Keywords

Keywords/Phrases

Search In:

Publication Years