Login | Register

Image Segmentation and Adaptive Contrast Enhancement for Haze Removal

Title:

Image Segmentation and Adaptive Contrast Enhancement for Haze Removal

Wang, Chunyan and Zhu, Bao (2020) Image Segmentation and Adaptive Contrast Enhancement for Haze Removal. In: 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE.

[thumbnail of Haze-removal.pdf]
Preview
Text (application/pdf)
Haze-removal.pdf - Accepted Version
Available under License Spectrum Terms of Access.
1MB

Official URL: https://doi.org/10.1109/MWSCAS48704.2020.9184525

Abstract

With a view to restoring image details of heavily hazy images, we propose an adaptive contrast enhancement algorithm specifically for haze removal. It is composed of 3 parts. The first part is to segment the input image into flat background of air space and foreground which is the rest of the image. A specific gradient matrix is defined to generate a gradient feature value to identify the pixels of very weak signals with the presence of noise of similar amplitude. In the second part, a CLAHE-based method is developed and applied to the foreground to provide a stronger enhancement to weaker signal variations while the background is protected from noise enhancement. A specifically designed filter is then applied to remove noise caused by the discontinuity between the foreground and background areas, while preserving the enhanced image details. The proposed algorithm has been tested and its effectiveness has been proven by the test results.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Book Section
Refereed:Yes
Authors:Wang, Chunyan and Zhu, Bao
Date:August 2020
Digital Object Identifier (DOI):10.1109/MWSCAS48704.2020.9184525
ID Code:994655
Deposited By: Chunyan Wang
Deposited On:08 Oct 2024 16:07
Last Modified:08 Oct 2024 16:07
Related URLs:
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top