A Modified Structural Similarity Index With Low Computational Complexity
Structural Similarity Index (SSIM) has been a benchmark method for image quality assessment (IQA). This is due to its simplicity and good performance. In this paper, we propose a modified SSIM method that reduces the computational complexity with comparable performance. Instead of computing simil...
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| Main Authors: | , |
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| Format: | Proceeding |
| Language: | English English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/28483/5/A%20MODIFIED.pdf http://ir.unimas.my/id/eprint/28483/3/ISPACS%202019_Program%20Book%20-%20Copy.pdf http://ir.unimas.my/id/eprint/28483/ https://ieeexplore.ieee.org/xpl/conhome/1001126/all-proceedings |
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| Summary: | Structural Similarity Index (SSIM) has been a
benchmark method for image quality assessment (IQA). This is due to its simplicity and good performance. In this paper, we propose a modified SSIM method that reduces the
computational complexity with comparable performance.
Instead of computing similarities on local windows, the
proposed method computes global information similarities. The proposed method omits the luminance part similarities in SSIM due to its less crucial role in assessing image quality. From the presented results, the proposed method has a much lower computational time and comparable performance compared to SSIM. |
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