| ▼Vision Functions | These are the base vision functions supported in OpenVX 1.1 |
| Absolute Difference | Computes the absolute difference between two images. The output image dimensions should be the same as the dimensions of the input images |
| Accumulate | Accumulates an input image into output image. The accumulation image dimensions should be the same as the dimensions of the input image |
| Accumulate Squared | Accumulates a squared value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image |
| Data Object Copy | Copy a data object to another |
| Accumulate Weighted | Accumulates a weighted value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image |
| Arithmetic Addition | Performs addition between two images. The output image dimensions should be the same as the dimensions of the input images |
| Arithmetic Subtraction | Performs subtraction between two images. The output image dimensions should be the same as the dimensions of the input images |
| Bitwise AND | Performs a bitwise AND operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
| Bitwise EXCLUSIVE OR | Performs a bitwise EXCLUSIVE OR (XOR) operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
| Bitwise INCLUSIVE OR | Performs a bitwise INCLUSIVE OR operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
| Bitwise NOT | Performs a bitwise NOT operation on a VX_DF_IMAGE_U8 input image. The output image dimensions should be the same as the dimensions of the input image |
| Box Filter | Computes a Box filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
| Non-Maxima Suppression | Find local maxima in an image, or otherwise suppress pixels that are not local maxima |
| Canny Edge Detector | Provides a Canny edge detector kernel. The output image dimensions should be the same as the dimensions of the input image |
| Channel Combine | Implements the Channel Combine Kernel |
| Channel Extract | Implements the Channel Extraction Kernel |
| Color Convert | Implements the Color Conversion Kernel. The output image dimensions should be the same as the dimensions of the input image |
| Convert Bit depth | Converts image bit depth. The output image dimensions should be the same as the dimensions of the input image |
| Custom Convolution | Convolves the input with the client supplied convolution matrix. The output image dimensions should be the same as the dimensions of the input image |
| Dilate Image | Implements Dilation, which grows the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image |
| Equalize Histogram | Equalizes the histogram of a grayscale image. The output image dimensions should be the same as the dimensions of the input image |
| Erode Image | Implements Erosion, which shrinks the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image |
| Fast Corners | Computes the corners in an image using a method based upon FAST9 algorithm suggested in [3] and with some updates from [4] with modifications described below |
| Gaussian Filter | Computes a Gaussian filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
| Non Linear Filter | Computes a non-linear filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
| Harris Corners | Computes the Harris Corners of an image |
| Histogram | Generates a distribution from an image |
| Gaussian Image Pyramid | Computes a Gaussian Image Pyramid from an input image |
| Laplacian Image Pyramid | Computes a Laplacian Image Pyramid from an input image |
| Reconstruction from a Laplacian Image Pyramid | Reconstructs the original image from a Laplacian Image Pyramid |
| Integral Image | Computes the integral image of the input. The output image dimensions should be the same as the dimensions of the input image |
| Magnitude | Implements the Gradient Magnitude Computation Kernel. The output image dimensions should be the same as the dimensions of the input images |
| Mean and Standard Deviation | Computes the mean pixel value and the standard deviation of the pixels in the input image (which has a dimension width and height) |
| Median Filter | Computes a median pixel value over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
| Min, Max Location | Finds the minimum and maximum values in an image and a location for each |
| Min | Implements a pixel-wise minimum kernel. The output image dimensions should be the same as the dimensions of the input image |
| Max | Implements a pixel-wise maximum kernel. The output image dimensions should be the same as the dimensions of the input image |
| Optical Flow Pyramid (LK) | Computes the optical flow using the Lucas-Kanade method between two pyramid images |
| Phase | Implements the Gradient Phase Computation Kernel. The output image dimensions should be the same as the dimensions of the input images |
| Pixel-wise Multiplication | Performs element-wise multiplication between two images and a scalar value. The output image dimensions should be the same as the dimensions of the input images |
| Remap | Maps output pixels in an image from input pixels in an image |
| Scale Image | Implements the Image Resizing Kernel |
| Sobel 3x3 | Implements the Sobel Image Filter Kernel. The output images dimensions should be the same as the dimensions of the input image |
| TableLookup | Implements the Table Lookup Image Kernel. The output image dimensions should be the same as the dimensions of the input image |
| Thresholding | Thresholds an input image and produces an output Boolean image. The output image dimensions should be the same as the dimensions of the input image |
| Warp Affine | Performs an affine transform on an image |
| Warp Perspective | Performs a perspective transform on an image |
| Bilateral Filter | The function applies bilateral filtering to the input tensor |
| MatchTemplate | Compares an image template against overlapped image regions |
| LBP | Extracts LBP image from an input image. The output image dimensions should be the same as the dimensions of the input image |
| HOG | Extracts Histogram of Oriented Gradients features from the input grayscale image |
| HoughLinesP | Finds the Probabilistic Hough Lines detected in the input binary image |
| Tensor Multiply | Performs element wise multiplications on element values in the input tensor data with a scale |
| Tensor Add | Performs arithmetic addition on element values in the input tensor data |
| Tensor Subtract | Performs arithmetic subtraction on element values in the input tensor data |
| Tensor TableLookUp | Performs LUT on element values in the input tensor data |
| Tensor Transpose | Performs transpose on the input tensor |
| Tensor Convert Bit-Depth | Creates a bit-depth conversion node |
| Tensor Matrix Multiply | Creates a generalized matrix multiplication node |
| Control Flow | Defines the predicated execution model of OpenVX |
| ▼Basic Features | The basic parts of OpenVX needed for computation |
| ▼Objects | Defines the basic objects within OpenVX |
| Object: Reference | Defines the Reference Object interface |
| Object: Context | Defines the Context Object Interface |
| Object: Graph | Defines the Graph Object interface |
| Object: Node | Defines the Node Object interface |
| Object: Array | Defines the Array Object Interface |
| Object: Convolution | Defines the Image Convolution Object interface |
| Object: Distribution | Defines the Distribution Object Interface |
| Object: Image | Defines the Image Object interface |
| Object: LUT | Defines the Look-Up Table Interface |
| Object: Matrix | Defines the Matrix Object Interface |
| Object: Pyramid | Defines the Image Pyramid Object Interface |
| Object: Remap | Defines the Remap Object Interface |
| Object: Scalar | Defines the Scalar Object interface |
| Object: Threshold | Defines the Threshold Object Interface |
| Object: ObjectArray | An opaque array object that could be an array of any data-object (not data-type) of OpenVX except Delay and ObjectArray objects |
| Object: Tensor | Defines The Tensor Object Interface |
| ▼Administrative Features | Defines the Administrative Features of OpenVX |
| ▼Advanced Objects | Defines the Advanced Objects of OpenVX |
| Object: Array (Advanced) | Defines the advanced features of the Array Interface |
| ▼Object: Node (Advanced) | Defines the advanced features of the Node Interface |
| Node: Border Modes | Defines the border mode behaviors |
| Object: Delay | Defines the Delay Object interface |
| Object: Kernel | Defines the Kernel Object and Interface |
| Object: Parameter | Defines the Parameter Object interface |
| ▼Advanced Framework API | Describes components that are considered to be advanced |
| Framework: Node Callbacks | Allows Clients to receive a callback after a specific node has completed execution |
| Framework: Performance Measurement | Defines Performance measurement and reporting interfaces |
| Framework: Log | Defines the debug logging interface |
| Framework: Hints | Defines the Hints Interface |
| Framework: Directives | Defines the Directives Interface |
| Framework: User Kernels | Defines the User Kernels, which are a method to extend OpenVX with new vision functions |
| Framework: Graph Parameters | Defines the Graph Parameter API |
1.8.11 
