Enhancing the Performance of Optical Hardware through Software Applications: A Study

Rajani. D

Department of Electronics and Communication Engineering, Sree Venkateswara College of Engineering, Nellore, A.P. India.

Mahesh. B

Department of Electrical Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

ABSTRACT

The process of image demosaicing, essential for reconstructing full-colour images from incomplete colour samples obtained from a colour-filter array (CFA), has garnered renewed interest, particularly with the prevalent use of the Bayer pattern. This resurgence can be attributed to the growing availability of source codes and executables, facilitating reproducible research in the field. In this article, a thorough survey encompassing over fifty published works on demosaicing since 1999. The objective is to complement prior reviews and provide insights into the evolution and current landscape of demosaicing techniques. By addressing key issues and delineating fundamental differences among various approaches, a thorough overview of the field is made. A notable finding from the survey is the popularity of spatial demosaicing methods, where the initial step involves interpolating the luminance channel, followed by reconstructing the chrominance channels based on the recovered luminance information. The article highlights three crucial areas requiring additional research. Firstly, addressing the difficulty of demosaicking images with low spectral correlation is paramount, along with enhancing our comprehension of the trade-off between spatial correlation and spectral correlation. It is also found that there is a necessity for more comprehensive investigation into evaluating the performance of demosaicking algorithms, particularly concerning the utilization of reference images, and understanding supplementary components within the imaging pipeline.

Keywords:

Demosaicking, Bayer, Colour Filter Array (CFA), spatial demosaicing methods, luminance channel, chrominance channel, spatial correlation, spectral correlation.