A box blur is an image filter in which each pixel in the resulting image has a value equal to the average value of its neighboring pixels in the input image. It is a form of low-pass ("blurring") filter and is a convolution.
Due to its property of using equal weights it can be implemented using a much simpler accumulation algorithm which is significantly faster than using a sliding window algorithm.
Box blurs are frequently used to approximate a Gaussian blur. By the central limit theorem, if applied 3 times on the same image, a box blur approximates the Gaussian kernel to within about 3%, yielding the same result as a quadratic convolution kernel.
In the frequency domain, a box blur has zeros and negative components. That is, a sine wave with a period equal to the size of the box will be blurred away entirely and wavelengths shorter than the size of the box may be phase reversed, as seen when two bokeh circles touch to form a bright spot where there would be a dark spot between two bright spots in the original image.
Famous quotes containing the words box and/or blur:
“The distant box is open. A sound of grain
Poured over the floor in some eagerness we
Rise with the night let out of the box of wind.”
—John Ashbery (b. 1927)
“Television ... helps blur the distinction between framed and unframed reality. Whereas going to the movies necessarily entails leaving one’s ordinary surroundings, soap operas are in fact spatially inseparable from the rest of one’s life. In homes where television is on most of the time, they are also temporally integrated into one’s “real” life and, unlike the experience of going out in the evening to see a show, may not even interrupt its regular flow.”
—Eviatar Zerubavel, U.S. sociologist, educator. The Fine Line: Making Distinctions in Everyday Life, ch. 5, University of Chicago Press (1991)