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.

scholarly journals A Coordinate Displacement Compensation Based Quality Enhancement Method for Chroma Subsampling and Upsampling on VVC

2021 ◽  
Author(s):  
Kuo-Liang Chung
Keyword(s):  
Color Image ◽  
Research Direction ◽  
Quality Enhancement ◽  
Coding System ◽  
Server Side ◽  
Full Color ◽  
Screen Content ◽  
Enhancement Method ◽  
Client Side

<div>Prior to encoding an input RGB full-color image I<sup>RGB</sup>, at the server side, performing chroma subsampling on the converted chroma image is a necessary step. After receiving the decompressed subsampled chroma image and luma</div><div>image at the client side, performing chroma upsampling is also a necessary step for reconstructing the RGB full-color image. In this paper, we consider seven commonly used chroma subsampling methods, denoted by C<sub>s</sub>, and four widely used chroma upsampling methods, denoted by C<sub>u</sub>. For each combination c<sub>s</sub>-c<sub>u</sub> in C<sub>s</sub>xC<sub>u</sub>, we first utilize the moment balance law to analyze the coordinate displacement (CD) bias problem occurring in c<sub>s</sub>. Next, for the combination c<sub>s</sub>-c<sub>u</sub>, we analyze the CD bias problem occurring in the transition from the server side to the client side. Then, we explain why the CD bias problem degrades the quality of the reconstructed RGB full-color images in the current coding system. To remedy this CD bias problem, a CD compensationbased (CDC-based) quality enhancement method is proposed to improve the quality of the reconstructed images. To the best of our knowledge, this is the first work in this research direction. Based on the IMAX, Kodak, SCI (screen content images), and Video datasets, the comprehensive experimental results have demonstrated that on the newly released versatile video coding (VVC) platform VTM-12.0, the proposed CDC-based quality enhancement method in our augmented coding system can achieve substantial quality improvement for 17 combinations in C<sub>s</sub>xC<sub>u</sub>.</div>

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 A Coordinate Displacement Compensation Based Quality Enhancement Method for Chroma Subsampling and Upsampling on VVC

2021 ◽  
Author(s):  
Kuo-Liang Chung ◽  
Chen-Wei Kao
Keyword(s):  
Color Image ◽  
Research Direction ◽  
Quality Enhancement ◽  
Coding System ◽  
Server Side ◽  
Full Color ◽  
Screen Content ◽  
Enhancement Method ◽  
Client Side

<div>Prior to encoding an input RGB full-color image I<sup>RGB</sup>, at the server side, performing chroma subsampling on the converted chroma image is a necessary step. After receiving the decompressed subsampled chroma image and luma</div><div>image at the client side, performing chroma upsampling is also a necessary step for reconstructing the RGB full-color image. In this paper, we consider seven commonly used chroma subsampling methods, denoted by C<sub>s</sub>, and four widely used chroma upsampling methods, denoted by C<sub>u</sub>. For each combination c<sub>s</sub>-c<sub>u</sub> in C<sub>s</sub>xC<sub>u</sub>, we first utilize the moment balance law to analyze the coordinate displacement (CD) bias problem occurring in c<sub>s</sub>. Next, for the combination c<sub>s</sub>-c<sub>u</sub>, we analyze the CD bias problem occurring in the transition from the server side to the client side. Then, we explain why the CD bias problem degrades the quality of the reconstructed RGB full-color images in the current coding system. To remedy this CD bias problem, a CD compensationbased (CDC-based) quality enhancement method is proposed to improve the quality of the reconstructed images. To the best of our knowledge, this is the first work in this research direction. Based on the IMAX, Kodak, SCI (screen content images), and Video datasets, the comprehensive experimental results have demonstrated that on the newly released versatile video coding (VVC) platform VTM-12.0, the proposed CDC-based quality enhancement method in our augmented coding system can achieve substantial quality improvement for 17 combinations in C<sub>s</sub>xC<sub>u</sub>.</div>

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 Unpaired medical image colorization using generative adversarial network

2021 ◽  
Author(s):  
Yihuai Liang ◽  
Dongho Lee ◽  
Yan Li ◽  
Byeong-Seok Shin
Keyword(s):  
Loss Function ◽  
Medical Image ◽  
Color Image ◽  
Medical Images ◽  
Diagnostic Errors ◽  
Training Image ◽  
Input Image ◽  
Generative Adversarial Network ◽  
Adversarial Network

AbstractWe consider medical image transformation problems where a grayscale image is transformed into a color image. The colorized medical image should have the same features as the input image because extra synthesized features can increase the possibility of diagnostic errors. In this paper, to secure colorized medical images and improve the quality of synthesized images, as well as to leverage unpaired training image data, a colorization network is proposed based on the cycle generative adversarial network (CycleGAN) model, combining a perceptual loss function and a total variation (TV) loss function. Visual comparisons and experimental indicators from the NRMSE, PSNR, and SSIM metrics are used to evaluate the performance of the proposed method. The experimental results show that GAN-based style conversion can be applied to colorization of medical images. As well, the introduction of perceptual loss and TV loss can improve the quality of images produced as a result of colorization better than the result generated by only using the CycleGAN model.

scholarly journals A Coordinate Displacement Compensation Based Quality Enhancement Method for Chroma Subsampling and Upsampling on VVC

2021 ◽  
Author(s):  
Kuo-Liang Chung ◽  
Chen-Wei Kao
Keyword(s):  
Color Image ◽  
Research Direction ◽  
Quality Enhancement ◽  
Coding System ◽  
Server Side ◽  
Full Color ◽  
Screen Content ◽  
Enhancement Method ◽  
Client Side

<div>Prior to encoding an input RGB full-color image I<sup>RGB</sup>, at the server side, performing chroma subsampling on the converted chroma image is a necessary step. After receiving the decompressed subsampled chroma image and luma</div><div>image at the client side, performing chroma upsampling is also a necessary step for reconstructing the RGB full-color image. In this paper, we consider seven commonly used chroma subsampling methods, denoted by C<sub>s</sub>, and four widely used chroma upsampling methods, denoted by C<sub>u</sub>. For each combination c<sub>s</sub>-c<sub>u</sub> in C<sub>s</sub>xC<sub>u</sub>, we first utilize the moment balance law to analyze the coordinate displacement (CD) bias problem occurring in c<sub>s</sub>. Next, for the combination c<sub>s</sub>-c<sub>u</sub>, we analyze the CD bias problem occurring in the transition from the server side to the client side. Then, we explain why the CD bias problem degrades the quality of the reconstructed RGB full-color images in the current coding system. To remedy this CD bias problem, a CD compensationbased (CDC-based) quality enhancement method is proposed to improve the quality of the reconstructed images. To the best of our knowledge, this is the first work in this research direction. Based on the IMAX, Kodak, SCI (screen content images), and Video datasets, the comprehensive experimental results have demonstrated that on the newly released versatile video coding (VVC) platform VTM-12.0, the proposed CDC-based quality enhancement method in our augmented coding system can achieve substantial quality improvement for 17 combinations in C<sub>s</sub>xC<sub>u</sub>.</div>

scholarly journals Learning to Hallucinate Face Images via Component Generation and Enhancement

2017 ◽  
Author(s):  
Yibing Song ◽  
Jiawei Zhang ◽  
Shengfeng He ◽  
Linchao Bao ◽  
Qingxiong Yang
Keyword(s):  
High Resolution ◽  
State Of The Art ◽  
Ground Truth ◽  
Input Image ◽  
Two Stage ◽  
Face Hallucination ◽  
Fine Grained ◽  
Second Stage ◽  
Training Images ◽  
Face Images

We propose a two-stage method for face hallucination. First, we generate facial components of the input image using CNNs. These components represent the basic facial structures. Second, we synthesize fine-grained facial structures from high resolution training images. The details of these structures are transferred into facial components for enhancement. Therefore, we generate facial components to approximate ground truth global appearance in the first stage and enhance them through recovering details in the second stage. The experiments demonstrate that our method performs favorably against state-of-the-art methods.

Analysis and modification of graphic data compression algorithms

2020 ◽  
Vol 25 (4) ◽  
pp. 32-40
Author(s):  
Bouza M.K. ◽  
Keyword(s):  
Color Image ◽  
Jpeg 2000 ◽  
Black And White ◽  
Advantages And Disadvantages ◽  
Graphic Data ◽  
Full Color ◽  
Wide Range ◽  
Site Design ◽  
Lzw Algorithm

The article examines the algorithms for JPEG and JPEG-2000 compression of various graphic images. The main steps of the operation of both algorithms are given, their advantages and disadvantages are noted. The main differences between JPEG and JPEG-2000 are analyzed. It is noted that the JPEG-2000 algorithm allows re-moving visually unpleasant effects. This makes it possible to highlight important areas of the image and improve the quality of their compression. The features of each step of the algorithms are considered and the difficulties of their implementation are compared. The effectiveness of each algorithm is demonstrated by the example of a full-color image of the BSU emblem. The obtained compression ratios were obtained and shown in the corresponding tables using both algorithms. Compression ratios are obtained for a wide range of quality values from 1 to ten. We studied various types of images: black and white, business graphics, indexed and full color. A modified LZW-Lempel-Ziv-Welch algorithm is presented, which is applicable to compress a variety of information from text to images. The modification is based on limiting the graphic file to 256 colors. This made it possible to index the color with one byte instead of three. The efficiency of this modification grows with increasing image sizes. The modified LZW-algorithm can be adapted to any image from single-color to full-color. The prepared tests were indexed to the required number of colors in the images using the FastStone Image Viewer program. For each image, seven copies were obtained, containing 4, 8, 16, 32, 64, 128 and 256 colors, respectively. Testing results showed that the modified version of the LZW algorithm allows for an average of twice the compression ratio. However, in a class of full-color images, both algorithms showed the same results. The developed modification of the LZW algorithm can be successfully applied in the field of site design, especially in the case of so-called flat design. The comparative characteristics of the basic and modified methods are presented.

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.

scholarly journals An Effective Bicubic Convolution Interpolation-Based Iterative Luma Optimization for Enhancing Quality in Chroma Subsampling

2021 ◽  
Author(s):  
Kuo-Liang Chung ◽  
Chih-Yuan Huang ◽  
Chen-Wei Kao
Keyword(s):  
Iterative Method ◽  
Color Image ◽  
State Of The Art ◽  
Linear Interpolation ◽  
Distortion Function ◽  
Full Color ◽  
Screen Content ◽  
Modification Method ◽  
Convex Property

<div>Traditionally, prior to compressing an RGB full-color image, for each converted 2x2 CbCr block B<sup>CbCr</sup>, chroma subsampling only downsamples B<sup>CbCr</sup>, but without changing the luma block B<sup>Y</sup> at all. In the current research, a special linear interpolation-based, namely the COPY-based, chroma subsampling-first luma modification (CSFLM) study has attempted to change the luma block for enhancing the quality of the reconstructed RGB full-color image. In this paper, a fast and effective nonlinear interpolation, namely the bicubic convolution interpolation (BCI), based iterative luma modification method for CSFLM is proposed. In our iterative method, a BCI-based distortion function and its convex property proof are first provided. Next, based on the proposed convex distortion function, a pseudoinverse technique is applied to obtain the initial luma modification solution, and then an iterative method is proposed to improve the initial luma modification solution. Based on five testing image datasets, namely the IMAX, Kodak, SCI (screen content images), CI (classical images), and Video datasets, the thorough experimental results have demonstrated that on the newly released Versatile Video Coding (VVC) platform VTM-12.0, our iterative luma modification method achieves substantial quality, execution-time, and quality-bitrate tradeoff improvements when compared with the existing state-of-the-art methods.</div>

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