A Retinex Algorithm for Image Enhancement Based on Recursive Bilateral Filtering

2015 ◽  
Author(s):  
Di Li ◽  
Yadi Zhang ◽  
Pengcheng Wen ◽  
Linting Bai
Keyword(s):  
Image Enhancement ◽  
Bilateral Filtering ◽  
Retinex Algorithm

scholarly journals Image Enhancement for Surveillance Video of Coal Mining Face Based on Single-Scale Retinex Algorithm Combined with Bilateral Filtering

Symmetry ◽  
2017 ◽  
Vol 9 (6) ◽  
pp. 93 ◽  
Author(s):  
Lei Si ◽  
Zhongbin Wang ◽  
Rongxin Xu ◽  
Chao Tan ◽  
Xinhua Liu, ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Coal Mining ◽  
Bilateral Filtering ◽  
Surveillance Video ◽  
Single Scale ◽  
Retinex Algorithm ◽  
Mining Face

scholarly journals Improved Bilateral Filtering for a Gaussian Pyramid Structure-Based Image Enhancement Algorithm

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 258 ◽  
Author(s):  
Chang Lin ◽  
Hai-feng Zhou ◽  
Wu Chen
Keyword(s):  
Image Enhancement ◽  
Gaussian Function ◽  
Color Space ◽  
Human Observer ◽  
Bilateral Filtering ◽  
Saturation Intensity ◽  
Gaussian Pyramid ◽  
Retinex Algorithm ◽  
Reflection Component ◽  
Enhancement Algorithm

To address the problem of unclear images affected by occlusion from fog, we propose an improved Retinex image enhancement algorithm based on the Gaussian pyramid transformation. Our algorithm features bilateral filtering as a replacement for the Gaussian function used in the original Retinex algorithm. Operation of the technique is as follows. To begin, we deduced the mathematical model for an improved bilateral filtering function based on the spatial domain kernel function and the pixel difference parameter. The input RGB image was subsequently converted into the Hue Saturation Intensity (HSI) color space, where the reflection component of the intensity channel was extracted to obtain an image whose edges were retained and are not affected by changes in brightness. Following reconversion to the RGB color space, color images of this reflection component were obtained at different resolutions using Gaussian pyramid down-sampling. Each of these images was then processed using the improved Retinex algorithm to improve the contrast of the final image, which was reconstructed using the Laplace algorithm. Results from experiments show that the proposed algorithm can enhance image contrast effectively, and the color of the processed image is in line with what would be perceived by a human observer.

Gaussian Pyramid Transform Retinex Image Enhancement Algorithm Based on Bilateral Filtering

2020 ◽  
Vol 57 (16) ◽  
pp. 161019
Author(s):  
林昌 Lin Chang ◽  
周海峰 Zhou Haifeng ◽  
陈武 Chen Wu
Keyword(s):  
Image Enhancement ◽  
Bilateral Filtering ◽  
Gaussian Pyramid ◽  
Enhancement Algorithm

Probabilistic, Multi-Scale Fractional Tonal Correction Bilateral Filter-Based Hazy Image Enhancement

2020 ◽  
Vol 20 (02) ◽  
pp. 2050010
Author(s):  
U. A. Nnolim
Keyword(s):  
Image Enhancement ◽  
Fractional Order ◽  
Bilateral Filter ◽  
Experimental Results ◽  
Bilateral Filtering ◽  
Image Intensity ◽  
Multi Scale ◽  
Global Contrast ◽  
Color Enhancement ◽  
Color Cast

This paper describes an algorithm utilizing a modified multi-scale fractional order-based operator combined with a probabilistic tonal operator, adaptive color enhancement and bilateral filtering to process hazy and underwater images. The multi-scale algorithm complements the tonal operator by enhancing edges, preventing overexposure of bright image regions, while enhancing details in the dark areas. The addition of a previously developed global enhancement operator removes color cast and improves global contrast in underwater images. The color enhancement function augments the color results of the dehazing algorithm without distorting image intensity. Furthermore, the bilateral filter suppresses noise while preserving enhanced details/edges due to the multi-scale algorithm. Experimental results indicate that the proposed system yields comparable or better results than other algorithms from the literature.

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