An Improved Retinex low-illumination image enhancement algorithm

Shao-Chuan Wang, D. Gao, Yangping Wang, Song Wang
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引用次数: 2

Abstract

Low-illumination images are generally low-quality images. The retinex algorithm can cause halo artifacts and loss of details in processing. Therefore, an improved Retinex algorithm is proposed. Firstly, the HSI color space which is more in line with the human visual characteristics is selected instead of the RGB image, that is, the luminance component I is processed. Then, the illuminance image is estimated by using a guided filter that fuses the edge detection operator, and the edge detection operator can be better positioned. At the edge, an illuminance image with rich edge information can be obtained; after obtaining the illuminance image, the reflected image can be obtained by the Retinex principle, the obtained reflected image is subjected to low-rank decomposition, and the low-rank property of the image is used to suppress the enlarged halo and the enhancement process. Noise; finally, the visual effect is further improved by local contrast enhancement. Experiments show that the algorithm can effectively improve the brightness and contrast of the image, preserve the details of the image, and also suppress the noise interference in the enhancement process. The subjective visual effect and objective evaluation results of the image have also been greatly improved.
一种改进的Retinex低照度图像增强算法
低照度图像通常是低质量图像。retinex算法在处理过程中容易产生光晕伪影和细节丢失。为此,提出了一种改进的Retinex算法。首先,选择更符合人类视觉特征的HSI色彩空间代替RGB图像,即对亮度分量I进行处理。然后,利用融合了边缘检测算子的导频滤波器对照度图像进行估计,从而更好地定位边缘检测算子;在边缘处,可以得到具有丰富边缘信息的照度图像;在获得照度图像后,利用Retinex原理得到反射图像,对得到的反射图像进行低秩分解,利用图像的低秩特性抑制光晕放大和增强过程。噪音;最后通过局部对比度增强进一步改善视觉效果。实验表明,该算法可以有效地提高图像的亮度和对比度,保留图像的细节,并在增强过程中抑制噪声干扰。图像的主观视觉效果和客观评价结果也有了很大的提高。
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