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COMPRESSION TECHNIQUES FOR LOW RESOLUTION GRAPHICAL IMAGES

IP.com Disclosure Number: IPCOM000009738D
Original Publication Date: 2000-Jan-01
Included in the Prior Art Database: 2002-Sep-16
Document File: 2 page(s) / 110K

Publishing Venue

Motorola

Related People

Eric Parker: AUTHOR [+2]

Abstract

While many standards exist to compress graphi- cal images, these methods may not provide optimum compression when the image will be displayed on a low resolution device. Handheld devices, such as PDA's and pagers, can benefit from custom com- pression algorithms that are sensitive to the type of graphical image to be displayed, the screen resolu- tion, and the number of colors that need to be dis- played or can be displayed by the handheld device.

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MO-LA @

COMPRESSION TECHNIQUES FOR LOW RESOLUTION GRAPHICAL IMAGES

by Eric Parker and Dan Sommers

BACKGROUND

  While many standards exist to compress graphi- cal images, these methods may not provide optimum compression when the image will be displayed on a low resolution device. Handheld devices, such as PDA's and pagers, can benefit from custom com- pression algorithms that are sensitive to the type of graphical image to be displayed, the screen resolu- tion, and the number of colors that need to be dis- played or can be displayed by the handheld device.

  This paper will discuss two different graphical applications and the methods used to compress the images. The target device supports 240x180 pixels and supports 4 different gray scales.

MAP APPLICATION

  Many applications of RF devices that present graphical data will display building or similar maps that will show the user locations of interest and/or the location of the user. To transmit and /or store the map data, a compression algorithm will reduce the amount of bandwidth and memory required.

  An example of a map graphic of the Boynton Beach Mall is shown below:

  An efficient compression algorithm can take advantage of two characteristics unique fo map graphics:

  The map graphic can be represented in two col- ors only

  A high percentage of the data is horizontal and vertical lines

  The data can be best compressed by using vec- tor graphics in both the horizontal and vertical direc- tion, and by taking advantage of the fact that the maximum length of the vector will be 240 (the max- imum horizontal resolution of the device), a number that can be represented in one byte.

THE ALGORITHM OPERATES AS FOLLOWS:

  If we organize the graphical data in rows and columns, and for example purposes, we use black pixels on a white background, then:

For each row in uncompressed data

For each column in uncompressed data

If uncompressed data pixel = black

  Count number of adjacent black pixels in the horizontal direction (next columns)

  Count number of adj...