title: Green channel guiding denoising on bayer image.
abstract: Denoising is an indispensable function for digital cameras. In respect that noise is diffused during the demosaicking, the denoising ought to work directly on bayer data. The difficulty of denoising on bayer image is the interlaced mosaic pattern of red, green, and blue. Guided filter is a novel time efficient explicit filter kernel which can incorporate additional information from the guidance image, but it is still not applied for bayer image. In this work, we observe that the green channel of bayer mode is higher in both sampling rate and Signal-to-Noise Ratio (SNR) than the red and blue ones. Therefore the green channel can be used to guide denoising. This kind of guidance integrates the different color channels together. Experiments on both actual and simulated bayer images indicate that green channel acts well as the guidance signal, and the proposed method is competitive with other popular filter kernel denoising methods.
authors.affiliation: College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, China.
authors.forename: Xin
authors.identifier: 0000-0003-1173-6892
authors.initials: X
authors.lastname: Tan
authors.affiliation: College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, China.
authors.forename: Shiming
authors.identifier: 0000-0003-1345-2527
authors.initials: S
authors.lastname: Lai
authors.affiliation: College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, China.
authors.forename: Yu
authors.identifier: 0000-0003-0011-2435
authors.initials: Y
authors.lastname: Liu
authors.affiliation: College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, China.
authors.forename: Maojun
authors.initials: M
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*
references.citation: IEEE Trans Image Process. 2007 Aug;16(8):2080-95
references.pmid: 17688213
references.citation: IEEE Trans Image Process. 2005 Mar;14(3):360-9
references.pmid: 15762333
references.citation: IEEE Trans Image Process. 2009 Nov;18(11):2451-62
references.pmid: 19635701
references.citation: IEEE Trans Image Process. 2007 Oct;16(10):2515-25
references.pmid: 17926933
references.citation: IEEE Trans Image Process. 2009 Apr;18(4):797-812
references.pmid: 19273050
references.citation: IEEE Trans Image Process. 2006 Dec;15(12):3736-45
references.pmid: 17153947