A Research on X-Trans Patterned CMOS

2013 ◽  
Vol 705 ◽  
pp. 313-318
Author(s):  
Gwang Gil Jeon

In the last two decades, super-resolution and demosaicking have been researched actively. Generally, digital camera suffers from both color filtering and low spatial resolution. Therefore it is worth studying above issues. In this paper, we design filters to conduct super-resolution for digital camera. Bayer pattern has been widely used in digital camera. In this paper, we conduct experiments on X-Trans color filter array (CFA) pattern. Experimental results confirm that the proposed filters are effective for solving demosaicking issues.

2013 ◽  
Vol 21 (16) ◽  
pp. 18820 ◽  
Author(s):  
Barry K. Karch ◽  
Russell C. Hardie

Author(s):  
Suvit Poomrittigul ◽  
Masanori Ogawa ◽  
Masahiro Iwahashi ◽  
Hitoshi Kiya

In this paper, we propose a reversible color transform (RCT) for color images acquired through a Bayer pattern color filter array. One existing RCT with fixed coefficients is simple to implement. However, it is not adaptive to each of input images. Another existing RCT based on eigenvector of covariance matrix of color components, which is equivalent to Karhunen–Loève transform (KLT), is adaptive. However, it requires heavy computational load. We remove a redundant part of this existing method, utilizing fixed statistical relation between two green components at different locations. Comparing to the KLT-based existing RCT, it was observed that the proposed RCT keeps adaptability and has better coding performance, even though its computational load is reduced.


Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3423 ◽  
Author(s):  
Chiman Kwan ◽  
Jude Larkin ◽  
Bulent Ayhan

Low lighting images usually contain Poisson noise, which is pixel amplitude-dependent. More panchromatic or white pixels in a color filter array (CFA) are believed to help the demosaicing performance in dark environments. In this paper, we first introduce a CFA pattern known as CFA 3.0 that has 75% white pixels, 12.5% green pixels, and 6.25% of red and blue pixels. We then present algorithms to demosaic this CFA, and demonstrate its performance for normal and low lighting images. In addition, a comparative study was performed to evaluate the demosaicing performance of three CFAs, namely the Bayer pattern (CFA 1.0), the Kodak CFA 2.0, and the proposed CFA 3.0. Using a clean Kodak dataset with 12 images, we emulated low lighting conditions by introducing Poisson noise into the clean images. In our experiments, normal and low lighting images were used. For the low lighting conditions, images with signal-to-noise (SNR) of 10 dBs and 20 dBs were studied. We observed that the demosaicing performance in low lighting conditions was improved when there are more white pixels. Moreover, denoising can further enhance the demosaicing performance for all CFAs. The most important finding is that CFA 3.0 performs better than CFA 1.0, but is slightly inferior to CFA 2.0, in low lighting images.


Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 600
Author(s):  
Meidong Xia ◽  
Chengyou Wang ◽  
Wenhan Ge

In this paper, we propose a weights-based image demosaicking algorithm which is based on the Bayer pattern color filter array (CFA). When reconstructing the missing G components, the proposed algorithm uses weights based on posteriori gradients to mitigate color artifacts and distortions. Furthermore, the proposed algorithm makes full use of the correlation of R–B channels in high frequency when interpolating R/B values at B/R positions. Experimental results show that the proposed algorithm is superior to previous similar algorithms in composite peak signal-to-noise ratio (CPSNR) and subjective visual effect. The biggest advantage of the proposed algorithm is the use of posteriori gradients and the correlation of R–B channels in high frequency.


2005 ◽  
Vol 44 (10) ◽  
pp. 107003 ◽  
Author(s):  
Min Shao ◽  
Kenneth E. Barner ◽  
Russell C. Hardie

2013 ◽  
Vol 717 ◽  
pp. 501-505 ◽  
Author(s):  
Gwang Gil Jeon

This paper introduced a problem of the modified Bayer pattern color filter array (CFA). A demosaicking method is also known as color interpolation, which is a digital camera process employed to restore a full-color imagery from an image with missing color information. In general, a CFA pair contains two green pixels and one red and blue pixel (RGGB). However, there exist alternatives such as RRGB or RGBB. In this paper, we study the effect of three different color arrays. Simulation results show that the obtained filters give good performance.


2010 ◽  
Author(s):  
Jr Maschal ◽  
Young Robert A. ◽  
Reynolds S. S. ◽  
Krapels Joe ◽  
Fanning Keith ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document