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Image quality assessment, Eigen Value, Complement Feature.
An Eigen formulation is proposed for image quality assessment IQA. Each block is represented by an array composed of feature vectors (intensity/color at this stage). After attaching the complement feature(s), the auto-correlation matrix is computed for each block. The proposed full reference FR-IQA is simply the deviation of the Eigen values of the degraded image from that of the original image. Interestingly, the second largest Eigen value was sufficient to perform this comparison. Results and comparisons with SSIM and GMSD schemes on different types of degradation are demonstrated to show the effectiveness of the proposed schemes. Using TID2013 database, the proposed scheme outperforms SSIM. In addition, the proposed schemes is closer to the MOS score compared to GMSD; however, the correlation with MOS is inferior as illustrated in the tables. These results are concluded from the average behaviour on all the images using all degradations (with 5 levels) on the database.
Salah Ameer, " EQ: An Eigen Image Quality Assessment based on the Complement Feature", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.12, No.6, pp. 13-18, 2020. DOI: 10.5815/ijigsp.2020.06.02
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