Binary image in the context of Run-length encoding


Binary image in the context of Run-length encoding

Binary image Study page number 1 of 1

Play TriviaQuestions Online!

or

Skip to study material about Binary image in the context of "Run-length encoding"


⭐ Core Definition: Binary image

A binary image is a digital image that consists of pixels that can have one of exactly two colors, usually black and white. Each pixel is stored as a single bit — i.e. either a 0 or 1.

A binary image can be stored in memory as a bitmap: a packed array of bits. A binary image of 640 × 480 pixels has a file size of only 37.5 KiB, and most also compress well with simple run-length compression. A binary image format is often used in contexts where it is important to have a small file size for transmission or storage, or due to color limitations on displays or printers.

↓ Menu
HINT:

In this Dossier

Binary image in the context of DjVu

DjVu is a computer file format designed primarily to store scanned documents, especially those containing a combination of text, line drawings, indexed color images, and photographs. It uses technologies such as image layer separation of text and background/images, progressive loading, arithmetic coding, and lossy compression for bitonal (monochrome) images. This allows high-quality, readable images to be stored in a minimum of space, so that they can be made available on the web.

DjVu has been promoted as providing smaller files than PDF for most scanned documents. The DjVu developers report that color magazine pages compress to 40–70 kB, black-and-white technical papers compress to 15–40 kB, and ancient manuscripts compress to around 100 kB; a satisfactory JPEG image typically requires 500 kB. Like PDF, DjVu can contain an OCR text layer, making it easy to perform copy and paste and text search operations.

View the full Wikipedia page for DjVu
↑ Return to Menu

Binary image in the context of Grayscale

In digital photography, computer-generated imagery, and colorimetry, a grayscale (American English) or greyscale (Commonwealth English) image is one in which the value of each pixel holds no color information and only expresses a shade of gray. Pixel values are typically stored in the range 0 to 255 (black to white).

Grayscale images, are black-and-white or gray monochrome, and composed exclusively of shades of gray. The contrast ranges from black at the weakest intensity to white at the strongest. Grayscale images are distinct from one-bit bi-tonal black-and-white images, which, in the context of computer imaging, are images with only two colors: black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between.

View the full Wikipedia page for Grayscale
↑ Return to Menu

Binary image in the context of Dither

Dither or dithering is an intentionally applied form of noise used to randomize quantization error, preventing large-scale patterns such as color banding in images. Dither is routinely used in processing of both digital audio and video data, and is often one of the last stages of mastering audio to a CD.

A common use of dither is converting a grayscale image to black and white, so that the density of black dots in the new image approximates the average gray level in the original.

View the full Wikipedia page for Dither
↑ Return to Menu

Binary image in the context of JBIG

JBIG is an early lossless image compression standard from the Joint Bi-level Image Experts Group, standardized as ISO/IEC standard 11544 and as ITU-T recommendation T.82 in March 1993. It is widely implemented in fax machines. Now that the newer bi-level image compression standard JBIG2 has been released, JBIG is also known as JBIG1. JBIG was designed for compression of binary images, particularly for faxes, but can also be used on other images. In most situations JBIG offers between a 20% and 50% increase in compression efficiency over Fax Group 4 compression, and in some situations, it offers a 30-fold improvement.

JBIG is based on a form of arithmetic coding developed by IBM (known as the Q-coder) that also uses a relatively minor refinement developed by Mitsubishi, resulting in what became known as the QM-coder. It bases the probability estimates for each encoded bit on the values of the previous bits and the values in previous lines of the picture. JBIG also supports progressive transmission, which generally incurs a small overhead in bit rate (around 5%).

View the full Wikipedia page for JBIG
↑ Return to Menu

Binary image in the context of JBIG2

JBIG2 is an image compression standard for bi-level images, developed by the Joint Bi-level Image Experts Group. It is suitable for both lossless and lossy compression. According to a press release from the Group, in its lossless mode JBIG2 typically generates files 3–5 times smaller than Fax Group 4 and 2–4 times smaller than JBIG, the previous bi-level compression standard released by the Group. JBIG2 was published in 2000 as the international standard ITU T.88, and in 2001 as ISO/IEC 14492.

View the full Wikipedia page for JBIG2
↑ Return to Menu

Binary image in the context of Joint Bi-level Image Experts Group

The Joint Bi-level Image Experts Group (JBIG) was a group of experts nominated by national standards bodies and major companies to work to produce standards for bi-level image coding. The "joint" refers to its status as a committee working on both ISO and ITU-T standards. It was one of two sub-groups of ISO/IEC Joint Technical Committee 1, Subcommittee 29, Working Group 1 (ISO/IEC JTC 1/SC 29/WG 1), whose official title is Coding of still pictures.

The Joint Bi-level Image Experts Group created the JBIG and JBIG2 standards. The group often meets jointly with the JPEG committee, which typically meets three times annually.

View the full Wikipedia page for Joint Bi-level Image Experts Group
↑ Return to Menu