Image enhancement of Shack-Hartmann wavefront sensor with non-uniform illumination

2021 ◽  
Author(s):  
Peijia Jiang ◽  
Mengmeng Zhao ◽  
Wang Zhao ◽  
Shuai Wang ◽  
Ping Yang
Keyword(s):  
Image Enhancement ◽  
Wavefront Sensor ◽  
Uniform Illumination

Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

2014 ◽  
Vol 631-632 ◽  
pp. 470-473
Author(s):  
Wei Wei
Keyword(s):  
Image Enhancement ◽  
Image Binarization ◽  
Uniform Illumination ◽  
Excellent Performance ◽  
Gray Image ◽  
3D Terrain ◽  
Enhancement Method ◽  
Pca Algorithm

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

scholarly journals Low light image enhancement based on non-uniform illumination prior model

2019 ◽  
Vol 13 (13) ◽  
pp. 2448-2456
Author(s):  
Yahong Wu ◽  
Jieying Zheng ◽  
Wanru Song ◽  
Feng Liu
Keyword(s):  
Image Enhancement ◽  
Uniform Illumination ◽  
Low Light ◽  
Prior Model ◽  
Light Image

Dynamical stochastic resonance for non-uniform illumination image enhancement

2018 ◽  
Vol 12 (12) ◽  
pp. 2147-2152 ◽  
Author(s):  
Yongbin Zhang ◽  
Hongjun Liu ◽  
Nan Huang ◽  
Zhaolu Wang
Keyword(s):  
Image Enhancement ◽  
Stochastic Resonance ◽  
Uniform Illumination

Laboratory Wavefront Sensor For Speckle Image Enhancement

1988 ◽  
Author(s):  
Steven Krausman ◽  
Andy Jankevics ◽  
Larry Schmutz
Keyword(s):  
Image Enhancement ◽  
Wavefront Sensor ◽  
Speckle Image

scholarly journals Low and non-uniform illumination color image enhancement using weighted guided image filtering

2021 ◽  
Author(s):  
Qi Mu ◽  
Xinyue Wang ◽  
Yanyan Wei ◽  
Zhanli Li
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Image Filtering ◽  
Uniform Illumination ◽  
Color Distortion ◽  
Color Image Enhancement ◽  
Restoration Algorithm ◽  
Retinex Algorithm ◽  
Color Restoration ◽  
Guided Image Filtering

AbstractIn the state of the art, grayscale image enhancement algorithms are typically adopted for enhancement of RGB color images captured with low or non-uniform illumination. As these methods are applied to each RGB channel independently, imbalanced inter-channel enhancements (color distortion) can often be observed in the resulting images. On the other hand, images with non-uniform illumination enhanced by the retinex algorithm are prone to artifacts such as local blurring, halos, and over-enhancement. To address these problems, an improved RGB color image enhancement method is proposed for images captured under non-uniform illumination or in poor visibility, based on weighted guided image filtering (WGIF). Unlike the conventional retinex algorithm and its variants, WGIF uses a surround function instead of a Gaussian filter to estimate the illumination component; it avoids local blurring and halo artifacts due to its anisotropy and adaptive local regularization. To limit color distortion, RGB images are first converted to HSI (hue, saturation, intensity) color space, where only the intensity channel is enhanced, before being converted back to RGB space by a linear color restoration algorithm. Experimental results show that the proposed method is effective for both RGB color and grayscale images captured under low exposure and non-uniform illumination, with better visual quality and objective evaluation scores than from comparator algorithms. It is also efficient due to use of a linear color restoration algorithm.

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