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Merge pull request #306 from tonysyu/doc-negative-dtypes

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Discuss negative dtypes in user guide
This commit is contained in:
Johannes Schönberger
2012-09-10 00:26:39 -07:00
parent 1fc7729f9a 2c55732fba
commit 67a238d027
1 changed files with 20 additions and 2 deletions
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doc/source/user_guide/data_types.txt
+20 -2
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@@ -14,13 +14,13 @@ Data type Range
uint8 0 to 255
uint16 0 to 65535
uint32 0 to 2\ :sup:`32`
float 0 to 1
float -1 to 1
int8 -128 to 127
int16 -32768 to 32767
int32 -2\ :sup:`31` to 2\ :sup:`31` - 1
========= =================================
Note that float images are restricted to the range 0 to 1 even though the data
Note that float images are restricted to the range -1 to 1 even though the data
type itself can exceed this range; all integer dtypes, on the other hand, have
pixel intensities that can span the entire data type range. Currently, *64-bit
(u)int images are not supported*.
@@ -142,6 +142,24 @@ By default, ``rescale_intensity`` stretches the values of ``in_range`` to match
the range of the dtype.
Note about negative values
==========================
People very often represent images in signed dtypes, even though they only
manipulate the positive values of the image (e.g., using only 0-127 in an int8
image). For this reason, conversion functions *only spread the positive values*
of a signed dtype over the entire range of an unsigned dtype. In other words,
negative values are clipped to 0 when converting from signed to unsigned
dtypes. (Negative values are preserved when converting between signed dtypes.)
To prevent this clipping behavior, you should rescale your image beforehand::
>>> image = exposure.rescale_intensity(img_int32, out_range=(0, 2**31 - 1))
>>> img_uint8 = img_as_ubyte(image)
This behavior is symmetric: The values in an unsigned dtype are spread over
just the positive range of a signed dtype.
References
==========