Sampling analog signals cause aliasing interference if the signal has frequency components higher than the folding frequency, i.e., half the sampling frequency. This distortion originates in the folding of these higher frequency components into the lower signal frequency spectrum with interference as a result. Usually aliasing artifacts are avoided by analog low-pass filtering of the signal prior to digitization. However, in the area of digitizing video signals from a CCD-based sensor such anti-alias filter is not feasible. The problem grows in importance due to increasing resolution requirements in many imaging applications pushing for CCD technology. This contribution reports the ongoing research to minimize the effects of two alias-based distortions, i.e., noise and moire patterns. In fluoroscopy, the amount of x-ray photons contributing to the image is restricted because of dose regulations. Quantum noise is clearly present in the images. The impinging white x-ray photons are spectrally shaped by the MTF of the imaging system. The resulting spectrum extends beyond the spatial Nyquist frequency of the CCD sensor. Aliased noise structures obscure diagnostic detail and, especially in real-time sequences, are annoying to look at. Another alias-based distortion is due to the anti-scatter grid, which is applied in order to reduce the number of scattered x-ray photons contributing to the image. Scattered photons give rise to a low-frequency blur of the images. An anti-scatter grid consists of a large number of parallel lead stripes separated by x- ray opaque material which are focussed at the x ray point source. The grid period is in the same order of magnitude as the CCD pixel size which causes moire pattern distortion in the images. In this contribution we discuss the restoration of both distortions. Aliased noise is minimized following a Wiener-type filtering approach. The moire pattern is attacked by inverse filtering. The analysis and simulations are presented, applications on medical images are shown.