24 January 2011 Perceptually relevant evaluation of noise power spectra in adaptive pictorial systems
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Noise Power Spectra (NPS) are traditionally measured using uniform areas of tone. Adaptive algorithms, such as noise reduction, demosaicing, and sharpening, can modify their behavior based on underlying image structure. In particular, noise reduction algorithms may suppress noise more strongly in perfectly uniform areas than they would in those with modest variations, as found in actual pictorial images, and so yield unrepresentative NPS. This phenomenon would be similar in nature to the susceptibility of high-contrast-edges to adaptive sharpening and the subsequent over-estimation of effective pictorial modulation transfer function by some targets. Experimentation is described that examines the effect of modern adaptive noise reduction algorithms on the NPS of images containing ramps of varying gradient. Gradients are chosen based on a survey of consumer images from areas where noise is typically noticeable, such as blue sky, walls and faces. Although loss in performance of adaptive noise reduction is observed as gradients increase, the effect is perceptually small when weighted according to the frequency of occurrence of the gradients in pictorial imaging. The significant additional complexity of measuring gradient-based NPS does not appear to be justified; measuring NPS from uniform areas of tone should suffice for most perceptual work.
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Robin B. Jenkin, Robin B. Jenkin, Brian W. Keelan, Brian W. Keelan, "Perceptually relevant evaluation of noise power spectra in adaptive pictorial systems", Proc. SPIE 7867, Image Quality and System Performance VIII, 786708 (24 January 2011); doi: 10.1117/12.871848; https://doi.org/10.1117/12.871848


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