Our Newsletter


Pixels & Resolution

An Intro:

A pixel is generally thought of as the smallest single component of a digital image. The definition is highly context-sensitive. For example, there can be "printed pixels" in a page, or pixels carried by electronic signals, or represented by digital values, or pixels on a display device, or pixels in a digital camera (photosensor elements). This list is not exhaustive, and depending on context, there are several terms that are synonymous in particular contexts, such as pel, sample, byte, bit, dot, spot, etc. The term "pixels" can be used in the abstract, or as a unit of measure, in particular when using pixels as a measure of resolution, such as: 2400 pixels per inch, 640 pixels per line, or spaced 10 pixels apart.

The measures dots per inch(dpi)and pixels per inch(ppi) are sometimes used interchangeably, but have distinct meanings, especially for printer devices, where dpi is a measure of the printer's density of dot (e.g. ink droplet) placement. For example, a high-quality photographic image may be printed with 600 ppi on a 1200 dpi inkjet printer. Even higher dpi numbers, such as the 4800 dpi quoted by printer manufacturers since 2002, do not mean much in terms of achievable resolution. The more pixels used to represent an image, the closer the result can resemble the original. The number of pixels in an image is sometimes called the resolution, though resolution has a more specific definition. Pixel counts can be expressed as a single number, as in a "three-megapixel" digital camera, which has a nominal three million pixels, or as a pair of numbers, as in a "640 by 480 display", which has 640 pixels from side to side and 480 from top to bottom (as in a VGA display), and therefore has a total number of 640 × 480 = 307,200 pixels or 0.3 megapixels.

The pixels, or color samples, that form a digitized image (such as a JPEG file used on a web page) may or may not be in one-to-one correspondence with screen pixels, depending on how a computer displays an image.

In computing, an image composed of pixels is known as a bitmapped image or a raster image. The word raster originates from television scanning patterns, and has been widely used to describe similar halftone printing and storage techniques.

Bits per pixel:

The number of distinct colors that can be represented by a pixel depends on the number of bits per pixel (bpp). A 1 bpp image uses 1-bit for each pixel, so each pixel can be either on or off. Each additional bit doubles the number of colors available, so a 2 bpp image can have 4 colors, and a 3 bpp image can have 8 colors:

  • 1 bpp, 21 = 2 colors (monochrome)
  • 2 bpp, 22 = 4 colors
  • 3 bpp, 23 = 8 colors
...
  • 8 bpp, 28 = 256 colors
  • 16 bpp, 216 = 65,536 colors ("Highcolor" )
  • 24 bpp, 224 ≈ 16.7 million colors ("Truecolor")

For color depths of 15 or more bits per pixel, the depth is normally the sum of the bits allocated to each of the red, green, and blue components. Highcolor, usually meaning 16 bpp, normally has five bits for red and blue, and six bits for green, as the human eye is more sensitive to errors in green than in 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).

Megapixels:

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 image 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). The neologism sensel is sometimes used to describe the elements of a digital camera's sensor, since these are picture-detecting rather than picture-producing elements.

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, two of the three color channels for each sensor must be interpolated and 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.


Display resolutions:



All prices are in EUR. Copyright 2017 Orangedwarf.com. Powered by OrangeDwarf..."true excitement!"