CUVI Features
CUVI provides ready to use Imaging functionality super-accelerated on GPUs. With CUVI, you can instantly add supercomputing performance to your Imaging applications from Entertainment/Medical/Industrial or Defense domains with minimal code changes and absolutely no prior knowledge of GPU programming. With CUVI, your end users can benefit from enhanced user experience and improved processing speeds.
We also offer super-packs for specific applications (see below). You can take it and plug into your application yourself or you can ask our Imaging and GPU experts to CUVI enable your complete processing pipeline. See complete feature list here
Complete function list:
Add - Adds two images
Adjust - Equivalent to MATLAB's imadjust
AND - Logical Bitwise AND
BitConversion - Converts image pixel values from one data type to another
BorderMask - Masks image borders with custom intensity
ChannelMerge - Merges R, G and B Channel to form a color image
ChannelSplit - Splits a three channel image into R, G and B channels
Color2Gray - Converts an RGB image to gray scale using custom transform coefficients
ColorTwist - Applies a color twist matrix to an image
CountInRange - Counts the number of pixels within the given intensity range
Crop - Crops the desired portion of an image
Demosaic - Restores an RGB image from a gray-scale Bayer image
Divide - Divides pixel values of two image buffers
EigenValsVecs - Calculates eigen values and eigen vectors at each pixel in an image
Flip - Mirrors an image about a horizontal or vertical axis, or both
GoodFeaturesToTrack - selects N best points on a image using KLT or Harris
haarFwd - Performs one-level wavelet decomposition of an image using haar basis
haarInv - Performs one-level haar wavelet reconstruction of an image
HistEq - Performs histogram equalization
ImageBinary - Converts input image into a binary image based on threshold
ImageGradients - Calculates X and Y gradients of image
ImageFilter - Performs linear 1D and 2D image filtering
Max - Computes the maximum of image pixel values
MaxFilter - Filters an image using a max filter intensity values
Mean - Computes the mean of image pixel values
MeanStdDev - Computes the mean and standard deviation of image pixel values
Min - Computes the minimum of image pixel values
MinEigenVal - Calculates the minimum eigen value at each pixel in an image
Adjust - Equivalent to MATLAB's imadjust
AND - Logical Bitwise AND
BitConversion - Converts image pixel values from one data type to another
BorderMask - Masks image borders with custom intensity
ChannelMerge - Merges R, G and B Channel to form a color image
ChannelSplit - Splits a three channel image into R, G and B channels
Color2Gray - Converts an RGB image to gray scale using custom transform coefficients
ColorTwist - Applies a color twist matrix to an image
CountInRange - Counts the number of pixels within the given intensity range
Crop - Crops the desired portion of an image
Demosaic - Restores an RGB image from a gray-scale Bayer image
Divide - Divides pixel values of two image buffers
EigenValsVecs - Calculates eigen values and eigen vectors at each pixel in an image
Flip - Mirrors an image about a horizontal or vertical axis, or both
GoodFeaturesToTrack - selects N best points on a image using KLT or Harris
haarFwd - Performs one-level wavelet decomposition of an image using haar basis
haarInv - Performs one-level haar wavelet reconstruction of an image
HistEq - Performs histogram equalization
ImageBinary - Converts input image into a binary image based on threshold
ImageGradients - Calculates X and Y gradients of image
ImageFilter - Performs linear 1D and 2D image filtering
Max - Computes the maximum of image pixel values
MaxFilter - Filters an image using a max filter intensity values
Mean - Computes the mean of image pixel values
MeanStdDev - Computes the mean and standard deviation of image pixel values
Min - Computes the minimum of image pixel values
MinEigenVal - Calculates the minimum eigen value at each pixel in an image
MinFilter - Filters an image using a min filter
MinMax- Computes the minimum and maximum of image pixel values
Multiply - Multiplies pixel values of two image buffers
NOT - Performs a bitwise NOT operation on each pixel
OpticalFlowHS - Calculates flow of each image pixel in two frames using Horn-Schunck method
opticalFlowPyrLKDense - Calculates flow of each image pixel in two frames using pyramidal Lucas-Kanade method
OR - Combines corresponding pixels of two image buffers by a bitwise OR operation
Resize - Resizes input image using linear-interpolation
RGB2Gray - Converts an RGB image to gray scale using fixed transform coefficients
RGB2YUV - Convert RGB image to YUV color model
RGBA2Gray - Converts an RGBA image to gray scale using fixed transform
Rotate - Rotates an image about origin (0,0) or center
Subtract - Subtracts pixel values of two image buffers
Sum - Computes the sum of image pixel values
TrackFeatures - Tracks input features from frame 1 onto frame 2 using KLT method
Transpose - Takes Transpose of the image
XOR - Combines corresponding pixels of two image buffers by a bitwise XOR operation
YUV2RGB - Convert YUV color model to an RGB image
MinMax- Computes the minimum and maximum of image pixel values
Multiply - Multiplies pixel values of two image buffers
NOT - Performs a bitwise NOT operation on each pixel
OpticalFlowHS - Calculates flow of each image pixel in two frames using Horn-Schunck method
opticalFlowPyrLKDense - Calculates flow of each image pixel in two frames using pyramidal Lucas-Kanade method
OR - Combines corresponding pixels of two image buffers by a bitwise OR operation
Resize - Resizes input image using linear-interpolation
RGB2Gray - Converts an RGB image to gray scale using fixed transform coefficients
RGB2YUV - Convert RGB image to YUV color model
RGBA2Gray - Converts an RGBA image to gray scale using fixed transform
Rotate - Rotates an image about origin (0,0) or center
Subtract - Subtracts pixel values of two image buffers
Sum - Computes the sum of image pixel values
TrackFeatures - Tracks input features from frame 1 onto frame 2 using KLT method
Transpose - Takes Transpose of the image
XOR - Combines corresponding pixels of two image buffers by a bitwise XOR operation
YUV2RGB - Convert YUV color model to an RGB image
