Abstract: Estimating the spatial frequency response (SFR) of an image acquisition system or device from its output images is accomplished by a image processing system and method thereof even when the original scene content cannot be carefully controlled as in the laboratory method. The image processing system methodology assumes that the scene contains specified reference signals (e.g., step edges), but that the reference signals' location, orientation, contrast, mean gray level, and spatial extent in the corresponding digitized image(s) are unknown. Reference signal responses are searched for and extracted using a paradigm, culminating in a set of candidate responses which survive all the tests by scoring highest on the goodness metrics. These surviving candidate responses are each fit, alone or in groups, to ideal responses that would occur if the given reference signal was passed through likely system models.

Abstract: Estimating spatial noise characteristics associated with an image acquired from an unknown digital image acquisition device is accomplished by a method, or system, which: provides predetermined default spatial noise characteristic information of the unknown digital image acquisition device; gathers user information related to the spatial noise characteristics of the unknown digital image acquisition device; gathers, from the acquired image, image data related to the spatial noise characteristics of the unknown digital image acquisition device; generates replacement data in response to the user information and the image data; and updates the predetermined default spatial noise characteristic information with the replacement data.

Abstract: An image encoding/decoding apparatus for performing transform coding by a method in which blocking artifacts are suppressed or eliminated is disclosed in which encoded data, transmitted by the encoding apparatus, is converted into received image data terms which are subsequently overlap transformed into frequency coefficients for modification by means of a filtering operation utilizing a quantization error matrix. The quantization error matrix can be derived from quantization error data generated in the encoding unit, or can be provided as a look-up table in the decoding unit. The modified frequency coefficients are converted into reduced-noise image data terms for reconstruction into a digital image.