Reducing aliasing in images: a PDE-based diffusion revisited
Pattern Recognition
Machine learning to design full-reference image quality assessment algorithm
Image Communication
Reconstruction of 3d surface and restoration of flat document image from monocular image sequence
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Increasing image compression rate using steganography
Expert Systems with Applications: An International Journal
Image noise detection in global illumination methods based on fast relevance vector machine
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
Engineering Applications of Artificial Intelligence
Hybrid fractal image coding with quadtree-based progressive structure
Journal of Visual Communication and Image Representation
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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.