TIFF 6.0 Specification
Final—June 3, 1992
Section 15: Tiled Images
Introduction
Motivation
This section describes how to organize images into tiles instead of strips.
For low-resolution to medium-resolution images, the standard TIFF method of
breaking the image into strips is adequate. However high-resolution images can
be accessed more efficiently—and compression tends to work better—if the im-
age is broken into roughly square tiles instead of horizontally-wide but vertically-
narrow strips.
Relationship to existing fields
When the tiling fields described below are used, they replace the
StripOffsets, StripByteCounts, and RowsPerStrip fields.
Use of tiles will
therefore cause older TIFF readers to give up because they will have no way of
knowing where the image data is or how it is organized.
Do not
use both strip-
oriented and tile-oriented fields in the same TIFF file.
Padding
Tile size is defined by TileWidth and TileLength. All tiles in an image are the
same size; that is, they have the same pixel dimensions.
Boundary tiles are padded to the tile boundaries. For example, if TileWidth is 64
and ImageWidth is 129, then the image is 3 tiles wide and 63 pixels of padding
must be added to fill the rightmost column of tiles. The same holds for TileLength
and ImageLength. It doesn’t matter what value is used for padding, because good
TIFF readers display only the pixels defined by ImageWidth and ImageLength
and ignore any padded pixels. Some compression schemes work best if the pad-
ding is accomplished by replicating the last column and last row instead of pad-
ding with 0’s.
The price for padding the image out to tile boundaries is that some space is
wasted. But compression usually shrinks the padded areas to almost nothing.
Even if data is not compressed, remember that tiling is intended for large images.
Large images have lots of comparatively small tiles, so that the percentage of
wasted space will be very small, generally on the order of a few percent or less.
The advantages of padding an image to the tile boundaries are that implementa-
tions can be simpler and faster and that it is more compatible with tile-oriented
compression schemes such as JPEG. See Section 22.
Tiles are compressed individually, just as strips are compressed.
That is, each row
of data in a tile is treated as a separate “scanline” when compressing.
Compres-
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