Green Channel Guiding Denoising on Bayer Image

Joint Authors

Liu, Yu
Zhang, Maojun
Tan, Xin
Lai, Shiming

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-03-10

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

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.

American Psychological Association (APA)

Tan, Xin& Lai, Shiming& Liu, Yu& Zhang, Maojun. 2014. Green Channel Guiding Denoising on Bayer Image. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051843

Modern Language Association (MLA)

Tan, Xin…[et al.]. Green Channel Guiding Denoising on Bayer Image. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1051843

American Medical Association (AMA)

Tan, Xin& Lai, Shiming& Liu, Yu& Zhang, Maojun. Green Channel Guiding Denoising on Bayer Image. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051843

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1051843