Pregled bibliografske jedinice broj: 1111509
An Overview of Grayscale Image Colorization Methods
An Overview of Grayscale Image Colorization Methods // Proceedings ELMAR-2020 / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka (ur.).
Zagreb: Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2020. str. 109-112 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1111509 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
An Overview of Grayscale Image Colorization
Methods
Autori
Žeger, Ivana ; Grgić, Sonja
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings ELMAR-2020
/ Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka - Zagreb : Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2020, 109-112
ISBN
978-1-7281-5972-0
Skup
62nd International Symposium ELMAR-2020
Mjesto i datum
Zadar, Hrvatska, 14.09.2020. - 15.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Colorization ; Grayscale Image ; Color Image ; Scribble-based Methods ; Example-based Methods ; Deep Lerning Methods
Sažetak
Conversion of grayscale images to color images is a process of adding color to gray, monochrome images in a convincing, visually acceptable way. Nowadays, automated conversion is a challenging area that links machine and deep learning methods with art. Although many experts claim that grayscale images contain a special artistic value, lack of color can be considered as a loss of information. This paper presents an overview of methods and techniques that have been developed for grayscale image colorization. The paper provides a classification of relevant methods, explains the principles on which they are based and emphasizes their advantages and disadvantages. Special focus is put on methods that involve deep learning algorithms. The results show that deep learning colorization methods provide automated conversion and outperform other methods both in terms of quality and speed.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-1064 - Pametna platforma za daljinska istraživanja u okolišu i industriji primjenom milimetarskih valova (MMSENSE) (Bosiljevac, Marko, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb