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Efficient Gaussian blur with linear sampling by Daniel Rákos

Gaussian blur is an image space effect that is used to create a softly blurred version of the original image. This image then can be used by more sophisticated algorithms to produce effects like bloom, depth-of-field, heat haze or fuzzy glass. In this article I will present how to take advantage of the various properties of the Gaussian filter to create an efficient implementation as well as a technique that can greatly improve the performance of a naive Gaussian blur filter implementation by taking advantage of bilinear texture filtering to reduce the number of necessary texture lookups. While the article focuses on the Gaussian blur filter, most of the principles presented are valid for most convolution filters used in real-time graphics.

Sep 08, 2010 | Read article... | Permalink

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