颜色恢复和边缘保持的低照度图像超分辨率重建方法

Super resolution of low illumination image based on color restoration and edge preserving

针对常规图像超分辨率重建方法应用于低照度环境下的图像时存在纹理信息丢失、颜色偏移失真和重建性能退化等问题,提出了一种颜色恢复和边缘保持的低照度图像超分辨率重建方法。在锚定邻域回归(ANR)的图像超分辨率重建方法基础上引入颜色恢复和边缘保持的照度增强函数,从而提高图像内容和边缘纹理的显著性;选择最小加权二乘滤波作为中心环绕函数(WLS)以抑制高频特征退化;同时针对YCbCr颜色空间的Y通道分量采用边缘保持的照度增强函数计算其反射分量,进一步增强边缘纹理特征。实验结果表明,所提方法获得了更好的视觉效果,相比于其他方法,该方法峰值信噪比(PSNR)提高了63.15%、结构相似度(SSIM)提高了46.86%、感知质量(PI)提高了4.12%。

In order to overcome the problems of texture information loss,color offset distortion and reconstruction performance degradation in case of super resolution of images in low illumination environment,this paper proposed a super-resolution method of low illumination image based on color restoration and edge preservation.Based on anchored neighborhood regression(ANR),the method introduced the illuminance enhancement function of color restoration and edge preservation to improve the significance of image content and edge texture.Meanwhile,it selected the weighted least squares(WLS)as the central surround function to suppress the degradation of high-frequency features.Moreover,for the Y-channel component of YCbCr color space,it used the edge preserving illuminance enhancement function to calculate reflection component to further enhance the edge texture feature.The experimental results show that the proposed method achieves better visual effect.Compared with other methods,the PSNR of this method is improved by 63.15%,SSIM is improved by 46.86%and the perceived quality(PI)is improved by 4.12%.