Inheritance diagram for ColorCorrectionFeature:

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Public Member Functions
None	__init__ (self, ColorMatrixTransformationModule module)
	Creates a ColorCorrectionFeature for an existing color matrix transformation module.

bool	enabled (self)
	Indicates whether the feature is currently enabled.

None	enabled (self, bool value)
	Enables or disables the feature.

None	reset_to_default (self)
	Resets the color correction matrix to identity matrix.

numpy.ndarray	matrix (self)
	Gets the current color correction matrix.

None	matrix (self, numpy.ndarray matrix)
	Sets the color correction matrix.

Protected Attributes
	_module = module

Detailed Description

Color correction applies a 3x3 color correction matrix to the image.

Supported pixel formats

BGR8
BGRa8
RGB8
RGBa8
BGR10
BGRa10
RGB10
RGBa10
BGR12
BGRa12

RGB12
RGBa12

See the Pixel and Pixel Format Specifications for a detailed description of the pixel formats.

Color correction is typically used to convert colors from a camera sensor’s native RGB space to a standard color space, or to perform color balancing and correction.

When performing color correction, a 3x3 color correction matrix is applied to the color values of the image.

The color correction matrix is represented as a 3×3 float array::

+--------+--------+--------+
| m_00   | m_01   | m_02   |
+--------+--------+--------+
| m_10   | m_11   | m_12   |
+--------+--------+--------+
| m_20   | m_21   | m_22   |
+--------+--------+--------+

Each element m_ij defines how much of the input channel j contributes to the output channel i. For example, m_01 is the contribution of the green input to the red output.

The matrix is applied as follows:

red_value_out   = m_00 * red_value_in + m_01 * green_value_in + m_02 * blue_value_in;
green_value_out = m_10 * red_value_in + m_11 * green_value_in + m_12 * blue_value_in;
blue_value_out  = m_20 * red_value_in + m_21 * green_value_in + m_22 * blue_value_in;

where red_value_in, green_value_in, and blue_value_in are the input red, green, and blue channel values, respectively, and red_value_out, green_value_out, and blue_value_out are the corresponding corrected output values. All RGB values are normalized to the range [0.0, 1.0].