Dark Color Image Segmentation Method Integrated MRF & Retinex

Authors

Yongchun Miao, School of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, China;
Cheng Yan, School of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, China;

Abstract

Abstract: Given the interference from noise, poor quality and low identification of the night images, it is difficult to segment them by traditional color image segmentation method. Therefore, a novel dark color image segmentation method integrated MRF&Retinex was proposed. The -LPG-PCA filtering model was built to filter out noise of an image. The recovery function of the denoised image was constructed, before converting RGB color space to HSV color space, and the MRF & Retinex model was built for image enhancement and color correction operation. The denoised and enhanced color image was segmented by the MRF&FCM clustering method. The experimental results show that the algorithm can effectively enhance night images, eliminate noise as well as improve the peak signal noise ratio, and can achieve desirable results in dark color image segmentation.

Recommended Citation

Miao, Yongchun and Yan, Cheng (2020) "Dark Color Image Segmentation Method Integrated MRF & Retinex," Journal of System Simulation: Vol. 27: Iss. 10, Article 24.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/24

First Page

2387

Revised Date

2015-07-24

DOI Link

https://doi.org/

Last Page

2394

CLC

TP391.41

Recommended Citation

Miao Yongchun, Cheng Yan. Dark Color Image Segmentation Method Integrated MRF & Retinex[J]. Journal of System Simulation, 2015, 27(10): 2387-2394.