Researchers writing in the International Journal of Arts and Technology, have proposed the use of the affine transformation to improve the performance of the edge fusion algorithms for removing noise from digital photographs, specifically in the art world.
Lei Zhao of the School of Fine Arts and Design at Mudanjiang Normal University in Mudanjiang, China, demonstrates how noise can be reduced using this transformation by about 74 per cent. Smoothing is also greatly improved when compared to two well-known approaches – non-subsampled contourlet transform and hybrid particle swarm optimisation.
Noise in a photograph is a random variation of brightness or colour in the image. In monochrome print photography, noise is often referred to as grain and is sometimes a desirable artefact. It may well also be desirable in some context in digital photography or the scanning of otherwise low-noise photographic prints. More commonly, however, avoiding the generation of noise in an image is preferred but not always possible. For photographic images taken under low-light conditions and the requisite high camera sensitivity values (high ISO) inherent noise is almost unavoidable. Such noise may be manifest as a lack of clarity between areas that would otherwise be of high contrast or else appear as a random, fuzzy veil of purple speckles in a colour image, or grey specks in a monochrome image.
“The proposed fusion algorithm based on radiation transformation can better meet the requirements of edge fusion of art photography images,” the team writes. They add that they hope to further improve the smoothness of the fusion and improve the effect of the fused art photography image still further.
Zhao, L. (2020) ‘Edge fusion algorithm of art photography image based on affine transformation‘, Int. J. Arts and Technology, Vol. 12, No. 4, pp.301-316.
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