Next Article in Journal
Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging
Previous Article in Journal
High Resolution Full-Aperture ISAR Processing through Modified Doppler History Based Motion Compensation
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1236;

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation

School of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 03722, Korea
Medical Device Development Centre, Daegu-Gyeongbuk Medical Innovation Foundation, 80 Cheombok-Ro, Dong-gu, Daegu 41061, Korea
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 1 May 2017 / Revised: 25 May 2017 / Accepted: 26 May 2017 / Published: 28 May 2017
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [4817 KB, uploaded 28 May 2017]   |  


In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences. View Full-Text
Keywords: color filter array image sensor; spatial-temporal filter; video denoising; inter-channel correlation color filter array image sensor; spatial-temporal filter; video denoising; inter-channel correlation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Lee, M.S.; Park, S.W.; Kang, M.G. Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation. Sensors 2017, 17, 1236.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top