CUDA Image Blur

GPU Teaching Kit – Accelerated Computing

Objective

The purpose of this lab is to implement an efficient image blurring algorithm for an input image. Like the image convolution Lab, the image is represented as RGB float values. You will operate directly on the RGB float values and use a 3x3 Box Filter to blur the original image to produce the blurred image.

Prerequisites

Before starting this lab, make sure that:

Instructions

Edit the code in the code tab to perform the following:

Instructions about where to place each part of the code is demarcated by the //@@ comment lines.

Local Setup Instructions

The most recent version of source code for this lab along with the build-scripts can be found on the Bitbucket repository. A description on how to use the CMake tool in along with how to build the labs for local development found in the README document in the root of the repository.

The executable generated as a result of compiling the lab can be run using the following command:

./ImageBlur_Template -e <expected.ppm> -i <input.ppm> \
  -o <output.ppm> -t image

where <expected.ppm> is the expected output, <input.ppm> is the input dataset, and <output.ppm> is an optional path to store the results. The datasets can be generated using the dataset generator built as part of the compilation process.