Image Quality Metrics: PSNR vs. SSIM
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Abstract
In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a simple mathematical relationship between them which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and jpeg2000 compression. A series of tests realized on images extracted from the Kodak database gives a better understanding of the similarity and difference between the SSIM and the PSNR.
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The record
- Venue
- Topic
- Image and Video Quality Assessment
- Field
- Computer Science
- Canadian institutions
- Université de Sherbrooke
- Funders
- —
- Keywords
- Peak signal-to-noise ratioArtificial intelligenceAdditive white Gaussian noiseJPEG 2000Image qualityComputer scienceJPEGPattern recognition (psychology)Similarity (geometry)Image (mathematics)Image compressionGaussian noiseGaussianComputer visionMeasure (data warehouse)MathematicsImage processingWhite noiseData mining
- Has abstract in OpenAlex
- yes