Izboljšava stresanja barv nizkoresolucijskih slik z omejeno barvno paleto

Švigelj, Mihael (author), Lebar Bajec, Iztok (mentor)

V delu se ukvarjamo s problematiko pretvorbe barvnih slik nizke resolucije v slike z omejeno, vnaprej določeno barvno paleto. Za čim boljše rezultate se za takšne probleme uporablja stresanje. Stresanje je koncept namernega dodajanja šuma, s katerim zmanjšamo prisotnost artefaktov in v splošnem dosežemo boljše rezultate. Predlagamo štiri nove tehnike stresanja, ki temeljijo na zaznavanju robov na sliki in jih podrobneje analiziramo. Dve izmed njih poleg dveh uveljavljenih metod stresanja primerjamo v anketi. Poleg različnih tehnik stresanja v anketi primerjamo tudi stresanje slik v štirih različnih barvnih prostorih — sRGB, CIELAB, ICtCp in Oklab. Iz rezultatov ankete prikažemo, da nove predlagane tehnike stresanja v večini primerov niso boljše od obstoječih. Pokažemo tudi, da je v veliki večini primerov stresanje v Oklab prostoru znatno boljše od stresanja v ostalih treh primerjanih prostorih. Rezultate ankete primerjamo z rezultati metrik DSCSI in FLIP in pokažemo visok nivo korelacije, kar kaže na primernost uporabe omenjenih metrik za analizo stresenih slik, kot tudi na primernost uporabe teh metrik za analizo slik, ki so stresene v barvnih prostorih, ki niso sRGB ali CIELAB, ki sta najpogosteje uporabljena. Na koncu predlagamo več potencialnih sprememb predlaganih algoritmov, ki bi lahko prinesle napredek v kakovosti stresenih slik.

• Language: Slovenian
• Keywords: stresanje barv, nizkoresolucijsko, paleta, barvni prostor, detekcija robov, anketa, sRGB, CIELAB, ICtCp, Oklab, Floyd, Steinberg, Burkes, Bayer
• Work type: Master's thesis/paper
• Typology: 2.09 - Master's Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2023
• PID: 20.500.12556/RUL-152942
• COBISS.SI-ID: 178665987
• Publication date in RUL: 13.12.2023

Secondary language

• Language: English
• Title: Improving color dithering in low resolution images with a limited color palette

Abstract

In this thesis, we deal with the problem of converting low-resolution color images into images of a limited, predetermined, color palette. To achieve the best results, dithering is used for such problems. Dithering is a concept of intentionally adding noise to reduce the presence of artifacts and generally achieve better results. We propose four new dithering techniques that are based on edge detection and analyze them in detail. Two of them, alongside two established dithering methods, are compared in a survey. In addition to different dithering techniques, we also compare images dithered in four different color spaces — sRGB, CIELAB, ICtCp, and Oklab. Survey results show that the new proposed dithering techniques are not better than the existing ones in most cases. They also show that in the vast majority of cases, dithering in Oklab space is significantly better than dithering in any of the other three spaces we compared. By comparing the survey results with the outputs of DSCSI and FLIP metrics we show a high level of correlation, indicating the suitability of using these metrics for analyzing dithered images, as well as the suitability of using these metrics for analyzing images that are dithered in color spaces other than sRGB or CIELAB, which are most commonly used. Finally, we propose several potential changes to the proposed algorithms that could bring progress in the quality of dithered images.

• Keywords: color dithering, low resolution, palette, color space, edge detection, survey, sRGB, CIELAB, ICtCp, Oklab, Floyd, Steinberg, Burkes, Bayer