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V4L2 FPGA/Examples/Convolutioner: Difference between revisions
V4L2 FPGA/Examples/Convolutioner (view source)
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This accelerator is capable of receiving a video frame from the kernel space, apply a Gaussian blurring through a convolution in space (custom kernel values are planned for future releases) and return the frame to the kernel. This operation allows reducing the noise on an image and correct minor errors. | This accelerator is capable of receiving a video frame from the kernel space, apply a Gaussian blurring through a convolution in space (custom kernel values are planned for future releases), and return the frame to the kernel. This operation allows reducing the noise on an image and correct minor errors. | ||
With multiple convolution accelerators, it is possible to perform more complex operations, such as demosaicing, Sobel, DoG (Differential of Gaussian), LoG (Laplacian of Gaussian), and other spatial filters. The code of the accelerator will be available after purchasing V4L2-FPGA and you can modify the code in order to implement other types of filters or increase the kernel size. | With multiple convolution accelerators, it is possible to perform more complex operations, such as demosaicing, Sobel, DoG (Differential of Gaussian), LoG (Laplacian of Gaussian), and other spatial filters. The code of the accelerator will be available after purchasing V4L2-FPGA and you can modify the code in order to implement other types of filters or increase the kernel size. | ||
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</gallery> | </gallery> | ||
The result has been zoom in to highlight the results. It is possible to | The result has been zoom in to highlight the results. It is possible to appreciate the blurring in the second image, which is the convolution output. | ||
'''Current throughput''' | '''Current throughput''' | ||