Image Processing Functions¶

`blurImage`¶

template<std::uint32_t filterSize = 1>
qVar_t<FixedPoint32<16>> qmath::blurImage(qVar_t<FixedPoint32<16>> qFrame)¶
Applies a 3x3 blur function on a qVar. The filter is.
* ┌           ┐
* │   1 2 1   │
* │   2 4 2   │  / 16
* │   1 2 1   │
* └           ┘
*
Return
qVar_t<FixedPoint32<16>> The blurred output of the tile

Parameters

qFrame: The input Frame tile

`sobelImage`¶

template<std::uint32_t filterSize = 1>
qVar_t<FixedPoint32<16>> qmath::sobelImage(qVar_t<FixedPoint32<16>> qFrame)¶
Applies a 3x3 sobel vertical edge detection. The filter is Vertical edge filter.
* ┌            ┐
* │  -1 -2 -1  │
* │   0  0  0  │  / 4
* │   1  2  1  │
* └            ┘
*
Horizontal edge filter
* ┌          ┐
* │  -1 0 1  │
* │  -2 0 2  │  / 4
* │  -1 0 1  │
* └          ┘
*
Return
qVar_t<FixedPoint32<16>> The vertical edges in the tile

Parameters

qFrame: The input Frame tile

`edgeImage3x3`¶

qVar_t<FixedPoint32<16>> qmath::edgeImage3x3(qVar_t<FixedPoint32<16>> qFrame)¶

Gets an image of all the adges in a tile calculated using the sobel filter.

Return
qVar_t<FixedPoint32<16>> The edge image tile

Parameters

qFrame: The input image tile

`imageResize`¶

template<typename OcmInputImageShape, typename OcmOutputImageShape>
void qmath::imageResize(OcmInputImageShape &ocmInputImage, OcmOutputImageShape &ocmOutputImage)¶
Reduces the size of a 3 channel image.

Assuming a BGR input image would look like
* ┌--------------------------------...-┐
* |BGR,BGR,|BGR,BGR,|BGR,BGR, ...      |
* |BGR,BGR,|BGR,BGR,|BGR,BGR, ...      |
* |--------------------------------...-|
* |BGR,BGR,|BGR,BGR,|BGR,BGR, ...      |
* |.                                   |
* |.                                   |
* |.                                   |
* └--------------------------------...-┘
*
The output is calculated as the average channel value in each of the 2x2 squares. A row of output is processed at a time, i.e. two rows of input is brought in. If the row is too large it is broken up into chunks based on maxOutTilesInBuffer(32)

Template Parameters

OcmInputImageShape: The shape of the input image with 3 channels

OcmOutputImageShape: The shape of the output image with 3 channels

Parameters

ocmInputImage: The input image tensor

ocmOutputImage: The output image tensor

`imageGrayscale`¶

template<typename OcmInputImageShape, typename OcmOutputImageShape>
void qmath::imageGrayscale(OcmInputImageShape &ocmInputImage, OcmOutputImageShape &ocmOutputImage, FixedPoint16<12> fxChannel1Weight = 0.114, FixedPoint16<12> fxChannel2Weight = 0.587, FixedPoint16<12> fxChannel3Weight = 0.299)¶
Converts a 3 channel image to grayscale, default values work best for a BGR input image.

Assuming a BGR input image would look like
* ┌------------------------------...-┐
* |BGR,BGR,BGR,BGR,BGR,BGR, ...      |
* |BGR,BGR,BGR,BGR,BGR,BGR, ...      |
* |------------------------------...-|
* |BGR,BGR,BGR,BGR,BGR,BGR, ...      |
* |.                                 |
* |.                                 |
* |.                                 |
* └------------------------------...-┘
*
The ouput is a weighted sum of the 3 channels for each pixel. Enough rows of the image are processed to fill out maxOutTilesInBuffer(128) unless one row does not fit into the buffer. In that case each row is broken up into multiple buffers to fill out maxOutTilesInBuffer

Template Parameters

OcmInputImageShape: The input image shape in (b,g,r) format

OcmOutputImageShape: The output image shape in (b,g,r) format

Parameters

ocmInputImage: The input image tensor

ocmOutputImage: The output image tensor

fxBlueWeight: The weight given to the blue channel. Default 0.114

fxGreenWeight: The weight given to the green channel. Default 0.587

fxRedWeight: The weight given to the red channel. Default 0.299