Further Improvement of Debayering Performance of RGBW Color Filter Arrays Using Deep Learning and Pansharpening Techniques

Autor: Chiman Kwan, Bryan Chou
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Imaging, Vol 5, Iss 8, p 68 (2019)
Druh dokumentu: article
ISSN: 2313-433X
DOI: 10.3390/jimaging5080068
Popis: The RGBW color filter arrays (CFA), also known as CFA2.0, contains R, G, B, and white (W) pixels. It is a 4 × 4 pattern that has 8 white pixels, 4 green pixels, 2 red pixels, and 2 blue pixels. The pattern repeats itself over the whole image. In an earlier conference paper, we cast the demosaicing process for CFA2.0 as a pansharpening problem. That formulation is modular and allows us to insert different pansharpening algorithms for demosaicing. New algorithms in interpolation and demosaicing can also be used. In this paper, we propose a new enhancement of our earlier approach by integrating a deep learning-based algorithm into the framework. Extensive experiments using IMAX and Kodak images clearly demonstrated that the new approach improved the demosaicing performance even further.
Databáze: Directory of Open Access Journals