低照度下平面图像舒适色度范围测定方法

为提升低照度条件下图像的视觉效果，提出了一种新的平面图像舒适色度范围测定方法。建立低照度平面图像增强去噪模型，通过联合双边过滤算法求解该模型后，结合熵值图像补偿方法，补偿增强去噪后低照度平面图像细节，将处理完成图像的颜色空间由RGB转化为HSV，并区分图像色度H中的显著与非显著部分，经显著部分左右视图色度转化后，通过主观评分平面显著图，完成低照度平面图像舒适色度范围测定。实验结果表明：所提方法增强去噪后的低照度图像更加清晰、减轻了模糊现象，可实现平面图像的舒适色度范围测定，且测定误差低。

Measuring Method for Comfortable Chromaticity Range of Plane Image under Low Illumination

In order to improve the visual effect of image under low illumination, a new method for measuring the comfortable chromaticity range of plane image is proposed. A low illuminance plane image enhancement denoising model is established. After solving the model through the joint bilateral filtering algorithm, combined with the entropy image compensation method, the details of the low illuminance plane image after enhancement denoising are compensated, the color space of the processed image is transformed from RGB to HSV, and the significant and non significant parts of the image chroma h are distinguished. After the chroma of the left and right views of the significant part is transformed, The comfortable chromaticity range of low illumination plane image is measured by subjective score plane saliency map. The experimental results show that the low illumination image after enhanced denoising is clearer, the blur is reduced, the comfortable chromaticity range of plane image can be measured, and the measurement error is low.