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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Image quality assessment in multiband DCT domain based on SSIM
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Image quality assessment in multiband DCT domain based on SSIM

机译：基于SSIM的多频带DCT域的图像质量评估

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摘要

The performance of image quality assessment method based on SSIM (structural similarity) is better than the PSNR (peak signal to noise ratio), but the assessment effects of SSIM is poor for seriously blurred image, therefore, the model that combined HVS (human visual sensitivity) and SSIM was established. The basic idea is based on the human eye's sensitivity to different frequency distortion image, the image is two-dimensional discrete cosine transform frequency component into low, mid, high-frequency component, to obtain the frequency component of light, contrast and structural information, using Pearson coefficient for weight and sum processing to the sub-image according to frequency bands of different sensitive degree, finally, get the sharpness of the image. Through nonlinear regression analysis of objective assessment and DMOS, experiments showed that this method was closer to human perception than SSIM and GSSIM for serious blurred distortion image. At the same time, compared to conventional algorithm MAE (mean absolute error), MSE (mean square error) and PSNR, this model was more consistent with human visual characteristics.
机译：基于SSIM（结构相似性）的图像质量评估方法的性能优于PSNR（峰值信噪比），但是对于严重模糊的图像，SSIM的评估效果较差，因此，将HVS（人眼）与人眼视觉相结合的模型灵敏度），并建立了SSIM。基本思想是基于人眼对不同频率失真图像的敏感性，该图像是将二维离散余弦变换频率分量转换为低，中，高频分量，以获得光的频率分量，对比度和结构信息，利用皮尔森系数对子图像根据不同敏感度的频带进行加权和求和处理，最终得到图像的清晰度。通过客观评估和DMOS的非线性回归分析，实验表明，对于严重的模糊失真图像，该方法比SSIM和GSSIM更接近于人类的感知。同时，与常规算法MAE（平均绝对误差），MSE（均方误差）和PSNR相比，该模型与人的视觉特征更加一致。

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