Research and Design of Color Restoration Algorithm for Demosaicing Bayer Pattern Images

2011 ◽  
Vol 130-134 ◽  
pp. 745-751
Author(s):  
Bo Zhu ◽  
De Sheng Wen ◽  
Wei Gao ◽  
Zong Xi Song ◽  
Hua Li
Keyword(s):  
Color Image ◽  
Chromatic Aberration ◽  
Interpolation Algorithm ◽  
Fpga Design ◽  
White Balance ◽  
Bayer Pattern ◽  
Cmos Sensor ◽  
Sequential Image ◽  
Color Restoration ◽  
Cfa Interpolation

This paper analyses the process of obtaining real color image based on a single CCD/CMOS sensor. Bayer CFA Interpolation algorithm and White Balance algorithm are presented. The proposed interpolation algorithm which can obtain better color image and is easier to implement by hardware is provided. In order to cancel chromatic aberration, one White Balance algorithm which aims at sequential image is presented and process of FPGA design is given. Experimental results show that the design works normally. The color of corrected picture is vivid compared to the real world.

Copy-Move Forgery Localization Using Convolutional Neural Networks and CFA Features

2018 ◽  
Vol 10 (4) ◽  
pp. 140-155 ◽  
Author(s):  
Lu Liu ◽  
Yao Zhao ◽  
Rongrong Ni ◽  
Qi Tian
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Color Filter ◽  
Interpolation Algorithm ◽  
Post Processing ◽  
Classification Result ◽  
Filter Array ◽  
Cfa Interpolation ◽  
Learned Features

This article describes how images could be forged using different techniques, and the most common forgery is copy-move forgery, in which a part of an image is duplicated and placed elsewhere in the same image. This article describes a convolutional neural network (CNN)-based method to accurately localize the tampered regions, which combines color filter array (CFA) features. The CFA interpolation algorithm introduces the correlation and consistency among the pixels, which can be easily destroyed by most image processing operations. The proposed CNN method can effectively distinguish the traces caused by copy-move forgeries and some post-processing operations. Additionally, it can utilize the classification result to guide the feature extraction, which can enhance the robustness of the learned features. This article, per the authors, tests the proposed method in several experiments. The results demonstrate the efficiency of the method on different forgeries and quantifies its robustness and sensitivity.

scholarly journals Color image zooming on the Bayer pattern

2005 ◽  
Vol 15 (11) ◽  
pp. 1475-1492 ◽  
Author(s):  
R. Lukac ◽  
K.N. Plataniotis ◽  
D. Hatzinakos
Keyword(s):  
Color Image ◽  
Bayer Pattern ◽  
Image Zooming

scholarly journals Colorimetric Analysis Using Scene-Adaptive Color Conversion Matrix of Calibrated CIS

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Sung-Hak Lee
Keyword(s):  
Transfer Matrix ◽  
Color Image ◽  
Image Sensors ◽  
Least Square ◽  
Colorimetric Analysis ◽  
White Balance ◽  
Polynomial Modeling ◽  
Conversion Matrix ◽  
Color Conversion ◽  
General Method

TheRGBsignals of different CISs (color image sensors) do not register the same values for the same viewing scene owing to their different spectral sensitivity and white balance mechanisms. Thus, CISs must be characterized based on CIE standard observation for colorimetric purposes. One general method for characterizing CISs is least square polynomial modeling to derive the colorimetric transfer matrix betweenRGBoutputs and CIEXYZtristimulus inputs. However, the transfer matrix that is obtained under the standard CIE illumination is unable to estimate various conditions of a CIS that is operated under various illuminations with varying chromaticity and luminance. Therefore, repeated experiments are necessary to obtain accurate colorimetric analysis results. This paper presents a scene-adaptive colorimetric analysis method using images captured by a general consumer camera under various environments.

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.

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