TY - JOUR
T1 - A Color Enhancement Scene Estimation Approach for Single Image Haze Removal
AU - Dharejo, Fayaz Ali
AU - Zhou, Yuanchun
AU - Deeba, Farah
AU - Du, Yi
N1 - Funding Information:
Manuscript received August 20, 2019; revised October 18, 2019; accepted October 28, 2019. Date of publication November 18, 2019; date of current version August 28, 2020. This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61836013 and in part by the National Key Research and Development Plan of China under Grant 2016YFB0501901. (Fayaz Ali Dharejo and Farah Deeba contributed equally to this work.) (Corresponding author: Yuanchun Zhou.) F. A. Dharejo, Y. Zhou, and Y. Du are with the Computer Network Information Center, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100190, China (e-mail: [email protected]; [email protected]; [email protected]).
Funding Information:
This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61836013 and in part by the National Key Research and Development Plan of China under Grant 2016YFB0501901.
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - The presence of suspended particles, such as fog, smoke, and dust, in the atmosphere reduces the quality of the captured image. It is essential to overcome these particles, because these particles have a very dire effect on different applications of image processing. We propose a new image dehazing method for remote sensing (RS) applications. Since the hazy RS image is affected by multiple colors and contrast reduction, our goal is to focus on degraded objects, including color correction and color-contrast enhancement. A 'Piecewise Linear Transformation (PWLT)' is used to correct the color distortion, and then the color contrast is improved by applying the proposed method. The intensity distribution manipulation is one of the most common methods used to strengthen image contrast in the past. Compared with advanced techniques, the proposed method is easy to implement and suitable for real-time applications. Moreover, it is not necessary to require prior imaging conditions. The experimental results show that, in terms of subjective and visual quality, the color, contrast, naturalness, and high brightness of the object increase in the image to be improved.
AB - The presence of suspended particles, such as fog, smoke, and dust, in the atmosphere reduces the quality of the captured image. It is essential to overcome these particles, because these particles have a very dire effect on different applications of image processing. We propose a new image dehazing method for remote sensing (RS) applications. Since the hazy RS image is affected by multiple colors and contrast reduction, our goal is to focus on degraded objects, including color correction and color-contrast enhancement. A 'Piecewise Linear Transformation (PWLT)' is used to correct the color distortion, and then the color contrast is improved by applying the proposed method. The intensity distribution manipulation is one of the most common methods used to strengthen image contrast in the past. Compared with advanced techniques, the proposed method is easy to implement and suitable for real-time applications. Moreover, it is not necessary to require prior imaging conditions. The experimental results show that, in terms of subjective and visual quality, the color, contrast, naturalness, and high brightness of the object increase in the image to be improved.
KW - Color correction
KW - dehazing
KW - low contrast
KW - optical contrast
KW - Piecewise Linear Transformation (PWLT)
UR - http://www.scopus.com/inward/record.url?scp=85090849263&partnerID=8YFLogxK
U2 - 10.1109/LGRS.2019.2951626
DO - 10.1109/LGRS.2019.2951626
M3 - Article
AN - SCOPUS:85090849263
SN - 1545-598X
VL - 17
SP - 1613
EP - 1617
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
IS - 9
M1 - 8903294
ER -