scholarly journals Demosaicing by Differentiable Deep Restoration

2021 ◽  
Vol 11 (4) ◽  
pp. 1649
Author(s):  
Jie Tang ◽  
Jian Li ◽  
Ping Tan
Keyword(s):  
Color Image ◽  
Superior Performance ◽  
Color Filter ◽  
Digital Cameras ◽  
Joint Learning ◽  
Selective Filter ◽  
Full Color ◽  
Spectrally Selective ◽  
Image Patches ◽  
The Difference

A mosaic of color filter arrays (CFAs) is commonly used in digital cameras as a spectrally selective filter to capture color images. The captured raw image is then processed by a demosaicing algorithm to recover the full-color image. In this paper, we formulate demosaicing as a restoration problem and solve it by minimizing the difference between the input raw image and the sampled full-color result. This under-constrained minimization is then solved with a novel convolutional neural network that estimates a linear subspace for the result at local image patches. In this way, the result in an image patch is determined by a few combination coefficients of the subspace bases, which makes the minimization problem tractable. This approach further allows joint learning of the CFA and demosaicing network. We demonstrate the superior performance of the proposed method by comparing it with state-of-the-art methods in both settings of noise-free and noisy data.

Image Quality Evaluation on Modified Bayer CFA

2013 ◽  
Vol 718-720 ◽  
pp. 2050-2054 ◽  
Author(s):  
Gwang Gil Jeon
Keyword(s):  
High Performance ◽  
Quality Evaluation ◽  
Color Image ◽  
Color Filter ◽  
Interpolation Algorithm ◽  
Digital Cameras ◽  
Full Color ◽  
Filter Array ◽  
Color Interpolation ◽  
Almost All

Almost all digital cameras adopt a color filter array to acquire images and requesting a demosaicking process of the sub-sampled color components to have the full color image. Thus, it is necessary to restore the CFA image correctly. Otherwise, perceptible color errors are presented. This paper proposes a color interpolation algorithm based on filter. The CFA we used is modified Bayer CFA. Simulation results show that the proposed method is effective and yield high performance in CPSNR and S-CIELAB.

scholarly journals Effective Three-Stage Demosaicking Method for RGBW CFA Images Using The Iterative Error-Compensation Based Approach

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3908
Author(s):  
Kuo-Liang Chung ◽  
Tzu-Hsien Chan ◽  
Szu-Ni Chen
Keyword(s):  
Error Compensation ◽  
Color Image ◽  
Ground Truth ◽  
Input Image ◽  
Previous Method ◽  
Color Filter ◽  
Second Stage ◽  
Full Color ◽  
Iterative Error

As the color filter array (CFA)2.0, the RGBW CFA pattern, in which each CFA pixel contains only one R, G, B, or W color value, provides more luminance information than the Bayer CFA pattern. Demosaicking RGBW CFA images I R G B W is necessary in order to provide high-quality RGB full-color images as the target images for human perception. In this letter, we propose a three-stage demosaicking method for I R G B W . In the first-stage, a cross shape-based color difference approach is proposed in order to interpolate the missing W color pixels in the W color plane of I R G B W . In the second stage, an iterative error compensation-based demosaicking process is proposed to improve the quality of the demosaiced RGB full-color image. In the third stage, taking the input image I R G B W as the ground truth RGBW CFA image, an I R G B W -based refinement process is proposed to refine the quality of the demosaiced image obtained by the second stage. Based on the testing RGBW images that were collected from the Kodak and IMAX datasets, the comprehensive experimental results illustrated that the proposed three-stage demosaicking method achieves substantial quality and perceptual effect improvement relative to the previous method by Hamilton and Compton and the two state-of-the-art methods, Kwan et al.’s pansharpening-based method, and Kwan and Chou’s deep learning-based method.

Automatic White Balance of Digital Camera Based on Global Probability Distribution

2012 ◽  
Vol 433-440 ◽  
pp. 5443-5447 ◽  
Author(s):  
Hui Nan Guo ◽  
Jian Zhong Cao
Keyword(s):  
Probability Distribution ◽  
Color Image ◽  
Digital Camera ◽  
Light Sources ◽  
Digital Cameras ◽  
White Balance ◽  
Hsi Color Model ◽  
The Difference ◽  
True Colors ◽  
Automatic White Balance

The white balance is an important parameter of digital camera which makes a great impact on the application of digital cameras. However, due to the limitations of hardware of digital camera, the output image of digital camera cannot restore true colors of the objects under the different light sources conditions. And existing automatic white balance (AWB) algorithms have many application restrictions, particularly the single color image, the algorithms always failure to adjust. To solve this problem, this paper proposes an optimized algorithm based on the gray world assumption and HSI color model. According to the R, G and B color components probability distribution, the algorithm adjusts the image by using the difference value of color. Experimental results show that our algorithm can adjust images in complex situations; meanwhile these confirm that this method is not only effective, but also has the advantage of easy realization.

scholarly journals The Effect of the Color Filter Array Layout Choice on State-of-the-Art Demosaicing

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3215 ◽  
Author(s):  
Ana Stojkovic ◽  
Ivana Shopovska ◽  
Hiep Luong ◽  
Jan Aelterman ◽  
Ljubomir Jovanov ◽  
...  
Keyword(s):  
Color Image ◽  
State Of The Art ◽  
Image Data ◽  
Linear Interpolation ◽  
Color Filter ◽  
Color Filter Array ◽  
Full Color ◽  
Design Choice ◽  
Filter Array ◽  
The One

Interpolation from a Color Filter Array (CFA) is the most common method for obtaining full color image data. Its success relies on the smart combination of a CFA and a demosaicing algorithm. Demosaicing on the one hand has been extensively studied. Algorithmic development in the past 20 years ranges from simple linear interpolation to modern neural-network-based (NN) approaches that encode the prior knowledge of millions of training images to fill in missing data in an inconspicious way. CFA design, on the other hand, is less well studied, although still recognized to strongly impact demosaicing performance. This is because demosaicing algorithms are typically limited to one particular CFA pattern, impeding straightforward CFA comparison. This is starting to change with newer classes of demosaicing that may be considered generic or CFA-agnostic. In this study, by comparing performance of two state-of-the-art generic algorithms, we evaluate the potential of modern CFA-demosaicing. We test the hypothesis that, with the increasing power of NN-based demosaicing, the influence of optimal CFA design on system performance decreases. This hypothesis is supported with the experimental results. Such a finding would herald the possibility of relaxing CFA requirements, providing more freedom in the CFA design choice and producing high-quality cameras.

scholarly journals Image Demosaicing Based on Generative Adversarial Network

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Jingrui Luo ◽  
Jie Wang
Keyword(s):  
Color Image ◽  
Color Filter ◽  
Digital Cameras ◽  
Data Preparation ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Filter Array ◽  
Discriminant Ability ◽  
Preparation Phase ◽  
Single Sensor

Digital cameras with a single sensor use a color filter array (CFA) that captures only one color component in each pixel. Therefore, noise and artifacts will be generated when reconstructing the color image, which reduces the resolution of the image. In this paper, we proposed an image demosaicing method based on generative adversarial network (GAN) to obtain high-quality color images. The proposed network does not need any initial interpolation process in the data preparation phase, which can greatly reduce the computational complexity. The generator of the GAN is designed using the U-net to directly generate the demosaicing images. The dense residual network is used for the discriminator to improve the discriminant ability of the network. We compared the proposed method with several interpolation-based algorithms and the DnCNN. Results from the comparative experiments proved that the proposed method can more effectively eliminate the image artifacts and can better recover the color image.

scholarly journals Full-color nanorouter for high-resolution imaging

Nanoscale ◽  
2021 ◽  
Author(s):  
Mingjie Chen ◽  
Long Wen ◽  
Dahui Pan ◽  
David Cumming ◽  
Xianguang Yang ◽  
...  
Keyword(s):  
High Resolution ◽  
Color Image ◽  
Image Sensors ◽  
Structural Color ◽  
High Resolution Imaging ◽  
Scaling Effects ◽  
Full Color ◽  
Resolution Imaging

Pixel scaling effects have been a major issue for the development of high-resolution color image sensors due to the reduced photoelectric signal and the color crosstalk. Various structural color techniques...

Assessment of different selective agar media for enumeration and isolation ofListeriafrom dairy products

1988 ◽  
Vol 55 (4) ◽  
pp. 579-583 ◽  
Author(s):  
Lucas Dominguez ◽  
José Francisco Fernández ◽  
Victor Briones ◽  
José Luis Blanco ◽  
Guillermo Suárez
Keyword(s):  
Dairy Products ◽  
Agar Medium ◽  
Raw Milk ◽  
Superior Performance ◽  
Direct Plating ◽  
Selective Agar ◽  
Natural Microflora ◽  
Agar Media ◽  
The Difference ◽  
Better Than

SummaryDifferent selective agar media were compared for the recovery and isolation of five species ofListeriafrom raw milk and cheese. The selective media examined were Beerens medium, MacBride medium and that described by Dominguezet al.(1984) with 6 mg/1 acriflavine, listeria selective agar medium (LSAM), and LSAM with 12 mg/1 acriflavine (LSAM × 2A); a non-selective yeast glucose Lemco agar was included for comparison. When the difference between listeria and the natural microflora of raw milk and cheese was 102cfu/ml, listeria could be isolated by direct plating on all media tested. When it was lower than 103–104cfu/ml, listeria were isolated by direct plating only on LSAM and LSAM × 2A. When the difference was greater than 104cfu/ml, a previous enrichment was necessary to isolate them. LSAM and LSAM × 2A media performed better than the other media tested for isolating listeria by direct plating and improved their isolation from dairy products. This superior performance was evaluated by the ability of these media to support colony formation of different species ofListeriatested, the easy recognition of these colonies from those formed by other microorganisms and by their capacity to inhibit the natural microflora of these foods.

scholarly journals Bionic Birdlike Imaging Using a Multi-Hyperuniform LED Array

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4084
Author(s):  
Xin-Yu Zhao ◽  
Li-Jing Li ◽  
Lei Cao ◽  
Ming-Jie Sun
Keyword(s):  
Imaging System ◽  
Color Image ◽  
Digital Camera ◽  
Frame Rate ◽  
Digital Cameras ◽  
Structured Illumination ◽  
Pixel Resolution ◽  
Led Array ◽  
Frequency Aliasing ◽  
Imaging Sensors

Digital cameras obtain color information of the scene using a chromatic filter, usually a Bayer filter, overlaid on a pixelated detector. However, the periodic arrangement of both the filter array and the detector array introduces frequency aliasing in sampling and color misregistration during demosaicking process which causes degradation of image quality. Inspired by the biological structure of the avian retinas, we developed a chromatic LED array which has a geometric arrangement of multi-hyperuniformity, which exhibits an irregularity on small-length scales but a quasi-uniformity on large scales, to suppress frequency aliasing and color misregistration in full color image retrieval. Experiments were performed with a single-pixel imaging system using the multi-hyperuniform chromatic LED array to provide structured illumination, and 208 fps frame rate was achieved at 32 × 32 pixel resolution. By comparing the experimental results with the images captured with a conventional digital camera, it has been demonstrated that the proposed imaging system forms images with less chromatic moiré patterns and color misregistration artifacts. The concept proposed verified here could provide insights for the design and the manufacturing of future bionic imaging sensors.

Designing a Color Filter with High Overall Transmittance for Improving the Color Accuracy of Digital Cameras

2021 ◽  
Vol 2021 (29) ◽  
pp. 1-6
Author(s):  
Yuteng Zhu ◽  
Graham D. Finlayson
Keyword(s):  
White Light ◽  
Digital Camera ◽  
Color Filter ◽  
Digital Cameras ◽  
Spectral Transmittance ◽  
Optimal Filters ◽  
Prior Art ◽  
Average Transmittance ◽  
Tristimulus Values ◽  
Correction Problem

Previously improved color accuracy of a given digital camera was achieved by carefully designing the spectral transmittance of a color filter to be placed in front of the camera. Specifically, the filter is designed in a way that the spectral sensitivities of the camera after filtering are approximately linearly related to the color matching functions (or tristimulus values) of the human visual system. To avoid filters that absorbed too much light, the optimization could incorporate a minimum per wavelength transmittance constraint. In this paper, we change the optimization so that the overall filter transmittance is bounded, i.e. we solve for the filter that (for a uniform white light) transmits (say) 50% of the light. Experiments demonstrate that these filters continue to solve the color correction problem (they make cameras much more colorimetric). Significantly, the optimal filters by restraining the average transmittance can deliver a further 10% improvement in terms of color accuracy compared to the prior art of bounding the low transmittance.

scholarly journals Enhancement of Satellite Imagesusing Image Sharpening Technique

2019 ◽  
Vol 8 (6S2) ◽  
pp. 351-354
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Histogram Equalization ◽  
Grayscale Image ◽  
Original Image ◽  
High Quality ◽  
Wide Range ◽  
Equalization Technique ◽  
The Difference

In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.

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