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Image quality can be assessed using objective or subjective methods. In the objective method, image quality assessments are performed by different algorithms that analyze the distortions and degradations introduced in an image. Subjective image quality assessments are a method based on the way in which humans experience or perceive image quality.
Pixels per inch (or pixels per centimetre) describes the detail of an image file when the print size is known. For example, a 100×100 pixel image printed in a 2 inch square has a resolution of 50 pixels per inch. Used this way, the measurement is meaningful when printing an image.
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.
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 ...
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The metric is based on initial work from the group of Professor C.-C. Jay Kuo at the University of Southern California. [1] [2] [3] Here, the applicability of fusion of different video quality metrics using support vector machines (SVM) has been investigated, leading to a "FVQA (Fusion-based Video Quality Assessment) Index" that has been shown to outperform existing image quality metrics on a ...
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