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Retinex based low-light image enhancement using guided filtering and variational framework 被引量:5

Retinex based low-light image enhancement using guided filtering and variational framework
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摘要 A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods. A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.
出处 《Optoelectronics Letters》 EI 2018年第2期156-160,共5页 光电子快报(英文版)
基金 supported by the China Scholarship Council Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX17_0776) the Natural Science Foundation of NUPT(No.NY214039)
关键词 图象 框架 过滤 颜色空间 改进算法 视觉效果 平均坡度 HSV RGB CLAHE Retinex based low-light image enhancement using guided filtering and variational framework HSV
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