A significant problem in computer graphics and digital photography is the presence of high-frequency “noise” in an image, which occurs in the form of random speckles or aberrant pixels that reduce the overall information content of the image especially when magnifying particular regions of the image for examination. The effect is manifest as a phenomenon known as aliasing and anti-aliasing techniques and filters are available to cope with it…to some extent.
Now, researchers in China have developed a new algorithm that utilises the distributed resources of cloud computing to sample blue noise and prevent image-distorting aliasing effects in a digital image. Their approach shows significant performance gains over conventional error-resilient encoding methods and native redundant encoding methods, they report.
Zhan, A., Hu, Y., Yu, M. and Zhang, Y. (2018) ‘A blue noise pattern sampling method based on cloud computing to prevent aliasing‘, Int. J. Innovative Computing and Applications, Vol. 9, No. 3, pp.173-179.