Image demosaicing: A systematic survey


Li X., GÜNTÜRK B. K., Zhang L.

Visual Communications and Image Processing 2008, San Jose, CA, United States Of America, 29 - 31 January 2008, vol.6822 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 6822
  • Doi Number: 10.1117/12.766768
  • City: San Jose, CA
  • Country: United States Of America
  • Istanbul Medipol University Affiliated: Yes

Abstract

Image demosaicing is a problem of interpolating full-resolution color images from so-called color-filter-array (CFA) samples. Among various CFA patterns, Bayer pattern has been the most popular choice and demosaicing of Bayer pattern has attracted renewed interest in recent years partially due to the increased availability of source codes/executables in response to the principle of "reproducible research". In this article, we provide a system-atic survey of over seventy published works in this field since 1999 (complementary to previous reviews22,67). Our review attempts to address important issues to demosaicing and identify fundamental differences among competing approaches. Our findings suggest most existing works belong to the class of sequential demosaicing - i.e., luminance channel is interpolated first and then chrominance channels are reconstructed based on recovered luminance information. We report our comparative study results with a collection of eleven competing algorithms whose source codes or executables are provided by the authors. Our comparison is performed on two data sets: Kodak PhotoCD (popular choice) and IMAX high-quality images (more challenging). While most existing demosaicing algorithms achieve good performance on the Kodak data set, their performance on the IMAX one (images with varying-hue and high-saturation edges) degrades significantly. Such observation suggests the importance of properly addressing the issue of mismatch between assumed model and observation data in demosaicing, which calls for further investigation on issues such as model validation, test data selection and performance evaluation. © 2008 SPIE-IS&T.