Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking
Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-ba...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-12-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/12/2787 |
| _version_ | 1828112666615349248 |
|---|---|
| author | Yusuke Monno Daisuke Kiku Masayuki Tanaka Masatoshi Okutomi |
| author_facet | Yusuke Monno Daisuke Kiku Masayuki Tanaka Masatoshi Okutomi |
| author_sort | Yusuke Monno |
| collection | DOAJ |
| description | Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. |
| first_indexed | 2024-04-11T11:54:03Z |
| format | Article |
| id | doaj.art-548b0831ede948a9830d482e2e66d865 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:54:03Z |
| publishDate | 2017-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-548b0831ede948a9830d482e2e66d8652022-12-22T04:25:13ZengMDPI AGSensors1424-82202017-12-011712278710.3390/s17122787s17122787Adaptive Residual Interpolation for Color and Multispectral Image DemosaickingYusuke Monno0Daisuke Kiku1Masayuki Tanaka2Masatoshi Okutomi3Department of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, JapanDepartment of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, JapanDepartment of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, JapanDepartment of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, JapanColor image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.https://www.mdpi.com/1424-8220/17/12/2787image sensorBayer color filter arraymultispectral filter arraydemosaickingresidual interpolation |
| spellingShingle | Yusuke Monno Daisuke Kiku Masayuki Tanaka Masatoshi Okutomi Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking Sensors image sensor Bayer color filter array multispectral filter array demosaicking residual interpolation |
| title | Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking |
| title_full | Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking |
| title_fullStr | Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking |
| title_full_unstemmed | Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking |
| title_short | Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking |
| title_sort | adaptive residual interpolation for color and multispectral image demosaicking |
| topic | image sensor Bayer color filter array multispectral filter array demosaicking residual interpolation |
| url | https://www.mdpi.com/1424-8220/17/12/2787 |
| work_keys_str_mv | AT yusukemonno adaptiveresidualinterpolationforcolorandmultispectralimagedemosaicking AT daisukekiku adaptiveresidualinterpolationforcolorandmultispectralimagedemosaicking AT masayukitanaka adaptiveresidualinterpolationforcolorandmultispectralimagedemosaicking AT masatoshiokutomi adaptiveresidualinterpolationforcolorandmultispectralimagedemosaicking |