OpenVX RGB June16

Copyright 2013-2018 The Khronos Group Inc.

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Contributors
  • Erik Rainey, Amazon

  • Frank Brill, Cadence

  • Jesse Villarrea, Texas Instruments

1. Extension Specification

This extension is intended to define the subset of behaviors and data types of the signed 16-bit support for OpenVX.

1.1. Changes to the OpenVX 1.1 Specification

The S16 extension enhances the input and output types per each kernel defined in the OpenVX 1.1 standard. The table below indicates the changes to each kernel for input and output.

Input and output argument types should be the same (e.g. input S16 and output S16) unless stated otherwise in the function description. In cases where having S16 inputs could lead to the overflow of S16 outputs, the behavior is analogous to what is currently in the standard for when the inputs are U8.

In the main standard, where the input is U8 and the output is also U8, then the output is converted according to the overflow policy in the function definition. Analogously, for this extension, where the inputs and outputs are both S16, the output is converted as necessary according to the overflow policy in the function definition.

In the main standard, where the input can be U8 and the output S16, the zero-extended answer is just written into the output. Analogously, for this extension, where the input can be S16 and the output S32, the sign-bit-extended result is written to the output.

1.2. Inputs

Vision Function U8 U16 S16 U32 S32 F32 color

AbsDiff

1.0

1.0.1

Accumulate

1.0

ext

AccumulateSquared

1.0

ext

AccumulateWeighted

1.0

ext

Add

1.0

1.0

And

1.0

ext

Box3x3

1.0

ext

CannyEdgeDetector

1.0

ext

ChannelCombine

1.0

ChannelExtract

1.0

ColorConvert

1.0

ConvertDepth

1.0

ext

1.0

ext

ext

Convolve

1.0

ext

Dilate3x3

1.0

EqualizeHistogram

1.0

ext

Erode3x3

1.0

FastCorners

1.0

ext

Gaussian3x3

1.0

ext

HarrisCorners

1.0

ext

HalfScaleGaussian

1.0

ext

Histogram

1.0

ext

IntegralImage

1.0

TableLookup

1.0

1.1

LaplacianPyramid

1.1

LaplacianReconstruct

1.1

Magnitude

1.0

MeanStdDev

1.0

ext

Median3x3

1.0

ext

MinMaxLoc

1.0

1.0

Multiply

1.0

1.0

NonLinearFilter

1.1

Not

1.0

ext

OpticalFlowPyrLK

1.0

ext

Or

1.0

ext

Phase

1.0

GaussianPyramid

1.0

ext

Remap

1.0

ext

ScaleImage

1.0

ext

Sobel3x3

1.0

ext

Subtract

1.0

1.0

Threshold

1.0

ext

WarpAffine

1.0

ext

WarpPerspective

1.0

ext

Xor

1.0

ext

1.3. Outputs

Vision Function U8 U16 S16 U32 S32 F32 color

AbsDiff

1.0

ext

1.0.1

Accumulate

1.0

ext

AccumulateSquared

1.0

ext

AccumulateWeighted

1.0

ext

Add

1.0

1.0

ext

And

1.0

ext

Box3x3

1.0

ext

CannyEdgeDetector

1.0

ext

ChannelCombine

1.0

ChannelExtract

1.0

ColorConvert

1.0

ConvertDepth

1.0

ext

1.0

ext

ext

Convolve

1.0

1.0

ext

Dilate3x3

1.0

EqualizeHistogram

1.0

ext

Erode3x3

1.0

FastCorners

1.0

Gaussian3x3

1.0

ext

HarrisCorners

1.0

HalfScaleGaussian

1.0

ext

Histogram

1.0

IntegralImage

1.0

TableLookup

1.0

1.1

LaplacianPyramid

1.1

LaplacianReconstruct

1.1

Magnitude

1.0

MeanStdDev

1.0

Median3x3

1.0

ext

MinMaxLoc

1.0

1.0

1.0

Multiply

1.0

1.0

ext

NonLinearFilter

1.1

Not

1.0

ext

OpticalFlowPyrLK

Or

1.0

ext

Phase

1.0

GaussianPyramid

1.0

ext

Remap

1.0

ext

ScaleImage

1.0

ext

Sobel3x3

1.0

ext

Subtract

1.0

1.0

ext

Threshold

1.0

ext

WarpAffine

1.0

ext

WarpPerspective

1.0

ext

Xor

1.0

ext

1.4. Vision Functions

The following sections describe additional changes and clarifications to existing kernel definitions beyond those already described in sections Inputs and Outputs.

1.4.1. Bitwise Operations

Referring to: AND, EXCLUSIVE OR, INCLUSIVE OR, and NOT.

All bit-wise operations on signed operands are executed in twos-complement representation of the values.

1.4.2. Custom Convolution

The current spec says if the input type is U8 and the output type is S16, then the output is simply the sum/scale. However, if the output type is U8, then the output saturates on both ends: 0 if sum/scale < 0, and 255 if sum/scale > 255. Analogously, S16 outputs should saturate to -32768 if sum/scale < -32768, and 32767 if sum/scale > 32767, and just sum/scale otherwise.

For VX_DF_IMAGE_S16 output, an additional step is taken:

\[output(x,y) = \begin{cases} -32768 & \text{if } sum / scale < -32768 \\ 32767 & \text{if } sum / scale > 32767 \\ sum / scale & \text{otherwise} \end{cases}\]

For VX_DF_IMAGE_S32 output, the summation is simply set to the output

output(x,y) = sum / scale

1.4.3. Fast Corners

When the input image is of type VX_DF_IMAGE_S16, the value of the intensity difference threshold strength_thresh. of type VX_TYPE_FLOAT32 must be within:

UINT16_MIN < t < UINT16_MAX