scholarly journals An Improved Demosaicking Algorithm Based On Region-Dividing

2020 ◽  
Vol 4 (5) ◽  
Author(s):  
Zheyuan Chen
Keyword(s):  
Image Quality ◽  
Experimental Results ◽  
Color Filter ◽  
Digital Cameras ◽  
Color Information ◽  
Color Filter Array ◽  
Filter Array ◽  
Color Channels

The Bayer Color Filter Array (CFA) is commonly used in such industries as digital cameras. However, due to the arrangement of color channels in the Bayer CFA, it becomes a problem to estimate the missed color information in each pixel. The algorithms that deal with this problem are named "demosaicking algorithms". There are many demosaicking algorithms, which show different efficiency and image quality for different images. This paper proposes an algorithm that combines two existing algorithms to reach better image qualities and acceptable computing complexities. The experimental results indicate effectiveness in terms of the balance between complexity and quality.

scholarly journals An Enhanced Lossless Color Filter Array Image Compression Based On Predictive Adaptive Arithmetic Coding

2015 ◽  
Vol 4 (1) ◽  
pp. 24
Author(s):  
L.M. Varalakshmi ◽  
R. Sowmiya
Keyword(s):  
Arithmetic Coding ◽  
Color Filter ◽  
Digital Cameras ◽  
Single Image ◽  
Color Information ◽  
Color Filter Array ◽  
Prediction Scheme ◽  
Filter Array ◽  
Adaptive Arithmetic Coding ◽  
Hierarchical Scheme

Most consumer digital cameras use a single image light sensor which provides color information using color filter array(CFA).This  provided a mosaic images, in which each pixel position contains only one color component in case of Bayer CFA Pattern. This paper produced a CFA hierarchical prediction scheme based on context adaptive coding. In CFA hierarchical scheme, the green pixels were subdivided into two sets .  was encoded by a gray scale conventional method and  was  predicted based on . The red pixels were predicted using both the sets of green pixels and blue pixels were predicted using red and green. The predictors were designed based on direction of the edges in the neighborhood. Using the prediction information, the magnitude of prediction error was also determined and context adaptive arithmetic coding was applied to reduce bits. The simulated results on CFA images showed that the proposed method gives less bits per pixel than the recently developed CFA compression algorithms.

scholarly journals Comparison of Denoising Algorithms for Demosacing Low Lighting Images Using CFA 2.0

2020 ◽  
Vol 11 (5) ◽  
pp. 37-60
Author(s):  
Chiman Kwan ◽  
Jude Larkin
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Poisson Noise ◽  
Color Filter ◽  
Digital Cameras ◽  
Critical Step ◽  
Lighting Conditions ◽  
Bayer Pattern ◽  
Filter Array ◽  
The Impact

In modern digital cameras, the Bayer color filter array (CFA) has been widely used. It is also widely known as CFA 1.0. However, Bayer pattern is inferior to the red-green-blue-white (RGBW) pattern, which is also known as CFA 2.0, in low lighting conditions in which Poisson noise is present. It is well known that demosaicing algorithms cannot effectively deal with Poisson noise and additional denoising is needed in order to improve the image quality. In this paper, we propose to evaluate various conventional and deep learning based denoising algorithms for CFA 2.0 in low lighting conditions. We will also investigate the impact of the location of denoising, which refers to whether the denoising is done before or after a critical step of demosaicing. Extensive experiments show that some denoising algorithms can indeed improve the image quality in low lighting conditions. We also noticed that the location of denoising plays an important role in the overall demosaicing performance.

A Research on X-Trans Patterned CMOS

2013 ◽  
Vol 705 ◽  
pp. 313-318
Author(s):  
Gwang Gil Jeon
Keyword(s):  
Spatial Resolution ◽  
Digital Camera ◽  
Super Resolution ◽  
Experimental Results ◽  
Color Filter ◽  
Color Filter Array ◽  
Bayer Pattern ◽  
Filter Array

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.

scholarly journals Further Improvements of CFA 3.0 by Combining Inpainting and Pansharpening Techniques

2020 ◽  
Vol 11 (6) ◽  
pp. 1-19
Author(s):  
Chiman Kwan ◽  
Jude Larkin
Keyword(s):  
Deep Learning ◽  
Color Filter ◽  
Digital Cameras ◽  
Color Filter Array ◽  
Filter Array

Color Filter Array (CFA) has been widely used in digital cameras. There are many variants of CFAs in the literature. Recently, a new CFA known as CFA 3.0 was proposed by us and has been shown to yield reasonable performance as compared to some standard ones. In this paper, we investigate the use of inpainting algorithms to further improve the demosaicing performance of CFA 3.0. Six conventional and deep learning based inpainting algorithms were compared. Extensive experiments demonstrated that one algorithm improved over other approaches.

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