Image Data Types and Ranges#

The oneIPL image processing functions support only absolute color images in which each pixel is represented by its channel intensities. The data storage for an image can be either pixel-oriented or plane-oriented (planar). For images in pixel order, all channel values for each pixel are clustered and stored consecutively, for example, RGBRGBRGB in case of an RGB image. The number of channels in a pixel-order image can be 1, 3, or 4.

For images in planar order, all image data for each channel is stored contiguously followed by the next channel, for example, RRR…GGG…BBB.

If the source and destination images are in the 4:2:0 interleaved layout (sub420i): all Y samples are found first in memory as an array of unsigned chars with an even number of lines memory alignment, followed by an array of unsigned chars containing interleaved U and V samples: YYYY… UVUV…

If the source and destination images are in the 4:2:0 non-interleaved layout (sub420): all Y samples are found first in memory as an array of unsigned chars with an even number of lines memory alignment, followed by a half-sized array of unsigned chars containing U samples and then, followed by a half-sized array of unsigned chars containing V samples: YYYY… UU… VV…

The image data type is specified as template parameter during ipl::image construction. The data may be signed, unsigned, or floating-point real. All channels in an image must have the same data type.

For example, in RGB image with std::uint8_t data type, three consecutive bytes (24 bits) per pixel represent the three channel intensities in the pixel mode (see RGB Image Formats for more details).

If an alpha (opacity) channel is present in image data, the image must have four channels, with alpha channel being the last one. The presence of the alpha channel can modify the function’s behavior. For such functions, oneIPL provides versions with and without alpha. If an alpha channel is specified, the operation usually is not performed on that channel. It is specified per function.

The range of values that can be represented by each data type lies between the lower and upper bounds. The following table lists data ranges and constant identifiers used in oneIPL to denote the respective range bounds:

Data Type	Lower Bound Identifier	Lower Bound Value	Upper Bound Identifier	Upper Bound Value
`int8_t`	`numerical_limits<int8_t>::min()`	-128	`numerical_limits<int8_t>::max()`	127
`uint8_t`	`numerical_limits<uint8_t>::min()`	0	`numerical_limits<uint8_t>::max()`	255
`int16_t`	`numerical_limits<int16_t>::min()`	-32768	`numerical_limits<int16_t>::max()`	32767
`uint16_t`	`numerical_limits<uint16_t>::min()`	0	`numerical_limits<uint16_t>::max()`	65535
`int32_t`	`numerical_limits<int32_t>::min()`	-2³¹	`numerical_limits<int32_t>::max()`	2³¹-1
`uint32_t`	`numerical_limits<uint32_t>::min()` -	0	`numerical_limits<uint32_t>::max()`	2³²-1
`float`^†	`numerical_limits<float>::min()`	1.175494351e^-38	`numerical_limits<float>::max()`	3.402823466e³⁸
`double`^†	`numerical_limits<double>::min()`	2.22507e^-308	`numerical_limits<double>::max()`	1.79769e³⁰⁸

^† The floating point range is for absolute values