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Technical
Native vs. logical pixels in LCDs Modern computer monitors are expected to display a range of resolutions (this was not always so, even with CRTs.) Displays capable of truly displaying only one resolution must first generate a native-resolution signal from any signal in a non-native resolution. Modern computer LCDs are designed with a native resolution which refers to the perfect match between pixels and triads. (CRT displays also use red-green-blue phosphor triads, but these are not coincident with image pixels, and cannot therefore be said to be equivalent to pixels.) The native resolution will produce the sharpest picture capable from the display. However, since the user can adjust the resolution, the monitor must be capable of displaying other resolutions. Non-native resolutions have to be supported by approximate resampling in the LCD controller, using interpolation algorithms. This often causes the screen to look somewhat jagged or blurry (especially with resolutions that are not even multiples of the native one.) For example, a display with a native resolution of 1280×1024 will look best set at 1280×1024 resolution, will display 800×600 adequately by drawing each pixel with more physical triads, and may be unable to display in 1600×1200 sharply due to the lack of physical triads. Pixels can be either rectangular or square. A number called the aspect ratio describes the squareness of a pixel. For example, a 1.25:1 aspect ratio means that each pixel is 1.25 times wider than it is high. Pixels on computer monitors are usually square, but pixels used in digital video have non-square aspect ratios, such as those used in the PAL and NTSC variants of the CCIR 601 digital video standard, and the corresponding anamorphic widescreen formats. Each pixel in a monochrome image has its own value, a correlate of perceptual brightness or physical intensity. A numeric representation of zero usually represents black, and the maximum value possible represents white. For example, in an eight-bit image, the maximum unsigned value that can be stored by eight bits is 255, so this is the value used for white. In a colour image, each pixel can be described using its hue, saturation, and value, but is usually represented instead as red, green and blue intensities (see RGB). Bits per pixel The number of distinct colours that can be represented by a pixel depends on the number of bits per pixel (bpp). The maximum number of colors a pixel can take can be found by taking two to the power of the color depth. For example, common values are Images composed of 256 colours or fewer are usually stored in the computer's video memory in chunky or planar format, where a pixel in memory is an index into a list of colours called a palette. These modes are therefore sometimes called indexed modes. While only 256 colours are displayed at once, those 256 colours are picked from a much larger palette, typically of 16 million colours. Changing the values in the palette permits a kind of animation effect. The animated startup logos of Windows 95 and Windows 98 are probably the best-known example of this kind of animation. On older systems, 4 bpp (16 colors) was common. For depths larger than 8 bits, the number is the sum of the bits devoted to each of the three RGB (red, green and blue) components. A 16-bit depth is usually divided into five bits for each of red and blue, and six bits for green, as most human eyes are more sensitive to green than the other two primary colors. For applications involving transparency, the 16 bits may be divided into five bits each of red, green, and blue, with one bit left for transparency. A 24-bit depth allows 8 bits per component. On some systems, 32-bit depth is available: this means that each 24-bit pixel has an extra 8 bits to describe its opacity (for purposes of combining with another image). When an image file is displayed on a screen, the number of bits per pixel is expressed separately for the raster file and for the display. Some raster file formats have a greater bit-depth capability than others. The GIF format, for example, has a maximum depth of 8 bits, while TIFF files can handle 48-bit pixels. There are no consumer display adapters that can output 48 bits of colour, so this depth is typically used for specialized professional applications with film scanners, printers and very expensive workstation computers. Such files are only rendered on screen with 24-bit depth on most computers. Subpixels Many display and image-acquisition systems are, for various reasons, not capable of displaying or sensing the different colour channels at the same site. This approach is generally resolved by using multiple subpixels, each of which handles a single color channel. For example, LCDs typically divide each pixel horizontally into three subpixels. Most LED displays divide each pixel into four subpixels; one red, one green, and two blue. Most digital camera sensors also use subpixels, by using colored filters. (CRT displays also use red-green-blue phosphor dots, but these are not aligned with image pixels, and cannot therefore be said to be subpixels). For systems with subpixels, two different approaches can be taken:
The latter approach has been used to increase the apparent resolution of colour displays. The technique, referred to as subpixel rendering, uses knowledge of pixel geometry to manipulate the three coloured sub-pixels separately, and is most effective with flat-panel displays set to their native resolutions (because the pixel geometry of such displays is usually fixed and predictable). This works best with black-on-white images and thus is often used to make text sharper and easier to read. An added bonus of this effect is that while it does not work on CRTs, it still produces an anti-aliasing effect, and thus still improves image quality to some extent. Megapixel A megapixel is 1 million pixels, and is a term used not only for the number of pixels in an image, but also to express the number of sensor elements of digital cameras or the number of display elements of digital displays. For example, a camera with an array of 2048×1536 sensor elements is commonly said to have "3.1 megapixels" (2048 × 1536 = 3,145,728). Digital cameras use photosensitive electronics, either Charge-coupled device (CCD) or Complementary metal–oxide–semiconductor (CMOS) image sensors, consisting of a large number of single sensor elements, each of which records a measured intensity level. In most digital cameras, the sensor array is covered with a patterned color filter mosaic having red, green, and blue regions in the Bayer filter arrangement, so that each sensor element can record the intensity of a single primary color of light. The camera interpolates the color information of neighboring sensor elements, through a process called demosaicing, to create the final image. These sensor elements are often called "pixels", even though they only record 1 channel (only red, or green, or blue) of the final color image. Thus, a so-called N-megapixel camera that produces an N-megapixel image provides only one-third of the information that an image of the same size could get from a scanner. Thus, certain color contrasts may look fuzzier than others, depending on the allocation of the primary colors (green has twice as many elements as red or blue in the Bayer arrangement). In contrast to conventional image sensors, the Foveon X3 sensor uses three layers of sensor elements, so that it detects red, green, and blue intensity at each array location. This structure eliminates the need for de-mosaicing and eliminates the associated image artifacts, such as color blurring around sharp edges. Citing the precedent established by mosaic sensors, Foveon counts each single-color sensor element as a pixel, even though the native output file size has only one pixel per three camera pixels*. With this method of counting, an N-megapixel Foveon X3 sensor therefore captures the same amount of information as an N-megapixel Bayer-mosaic sensor, though it packs the information into fewer image pixels, without any interpolation. Standard display resolutions Standard display resolutions include: Similar concepts Several other types of objects derived from the idea of the pixel, such as the voxel (volume element), texel (texture element) and surfel (surface element), have been created for other computer graphics and image processing uses. Etymology The word pixel was first published in 1965 by Frederic C. Billingsley of JPL, to describe the picture elements of video images from space probes to the moon and Mars; but he did not coin the term himself, and the person he got it from (Keith E. McFarland at the Link Division of General Precision in Palo Alto) does not know where he got it, but says it was "in use at the time" (circa 1963). The word is a combination of picture and element, via pix. Pix was first coined in 1932 in a headline in Variety magazine, as an abbreviation for the word pictures, in reference to movies; by 1938 pix was being used in reference to still pictures by photojournalists. The concept of a picture element dates to the earliest days of television, for example as Bildpunkt (the German word for pixel, literally picture point) in the 1888 German patent of Paul Nipkow. The earliest publication of the term picture element itself was in Wireless World magazine in 1927. A brief but detailed history of pixel and picture element, with references, is linked below. See also | ||||||||||||
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