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But when the pixel counts are referred to as "resolution", the convention is to describe the pixel resolution with the set of two positive integer numbers, where the first number is the number of pixel columns (width) and the second is the number of pixel rows (height), for example as 7680 × 6876.
The apparent PPI of a monitor depends upon the screen resolution (that is, the number of pixels) and the size of the screen in use; a monitor in 800×600 mode has a lower PPI than does the same monitor in a 1024×768 or 1280×960 mode.
(* The pixel number of 6,000x4,000 ist the number of "effective pixels". The sensor usually has a few extra rows of pixels on all four sides, which explains the sensor resolution of 24.3 MPixels often stated, but no information about the exact image size available.) 6,016 4,000 24,064,000 24.1 Nikon D3300 Canon M50: 6,048 4,032 24,385,536 24.4
One of the simpler ways of increasing the size, replacing every pixel with a number of pixels of the same color. The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest ...
Calculate the scaled pixel size as 1 ⁄ 96 in × (56/28) = 1 ⁄ 48 inch (0.53 mm). Calculate the DPI of the TV as 2160 / (30 in / √ 9^2 + 16^2 × 16) ≈ 82.61 dpi. Calculate the real-pixel count per logical-pixel as 1 ⁄ 48 in × 82.61 dpi ≈ 1.721 pixels. A browser will then choose to use the 1.721× pixel size, or round to a 2× ratio.
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In the case of decreasing the pixel number (scaling down), this usually results in a visible quality loss. From the standpoint of digital signal processing, the scaling of raster graphics is a two-dimensional example of sample-rate conversion, the conversion of a discrete signal from a sampling rate (in this case, the local sampling rate) to ...
Like any resampling operation, changing image size and bit depth are lossy in all cases of downsampling, such as 30-bit to 24-bit or 24-bit to 8-bit palette-based images. While increasing bit depth is usually lossless, increasing image size can introduce aliasing or other undesired artifacts.
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