This article deals with estimating the quality of natural color images from the digital image itself, for the purpose of determining whether the quality is sufficient for printing or displaying at some specified quality level. The problem of measuring simply defined parameters that correlate reasonably with human perception is discussed. Then an algorithm is described that measures sharpness, stochastic noise, and the blocking artifact of JPEG compression. The sharpness measure is the maximum of local sharpness, defined as the maximum gradient at an edge divided by the edge contrast. The algorithm behaves fairly consistently with respect to the amount of simulated blur and the measure correlates with the subjective sharpness of different images. The output of the stochastic noise algorithm is an unspecified number of noise levels, each of which is associated with the corresponding mean luminance. The algorithm computes a gradient image using the Sobel filters and uses the bivariate histogram of gradient and luminance to find the noise levels. The gradient filters are suitable for estimating the effect of power spectrum on noise visibility, but the discrimination between image details and noise is only partially solved by this method. The blocking artifact measure describes a characteristic spikiness in the histogram of the Sobel gradient.