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Visual information fidelity (VIF) is a full reference image quality assessment index based on natural scene statistics and the notion of image information extracted by the human visual system. [1] It was developed by Hamid R Sheikh and Alan Bovik at the Laboratory for Image and Video Engineering (LIVE) at the University of Texas at Austin in 2006
The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception -based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual ...
Image quality assessment is part of the quality of experience measures. Image quality can be assessed using two methods: subjective and objective. Subjective methods are based on the perceptual assessment of a human viewer about the attributes of an image or set of images, while objective methods are based on computational models that can ...
For example, a bitmap image may measure 1,000 × 1,000 pixels, a resolution of 1 megapixel. If it is labelled as 250 PPI, that is an instruction to the printer to print it at a size of 4 × 4 inches. Changing the PPI to 100 in an image editing program would tell the printer to print it at a size of 10 × 10 inches.
Image fidelity, often referred to as the ability to discriminate between two images [1] or how closely the image represents the real source distribution. [2] Different from image quality, which is often referred to as the subject preference for one image over another, image fidelity represents to the ability of a process to render an image accurately, without any visible distortion or ...
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