Abstract
Data inaccuracy due to amplitude quantization in digital imaging systems can be viewed as a form of random noise.The effect of this noise is to reduce the accuracy of decisions based on image data. Experimental results are presented to demonstrate the reduction in human-observer decision accuracy due to quantization noise in addition to white Gaussian noise. There is a significant reduction when the ratio Q/σp is greater than unity, where Q is the quantization-step amplitude and σp, is the standard deviation per pixel of the uncorrelated image noise.

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