Picture processing: 1976

The question of what spatial frequency response gives optimum image quality in computed tomography (CT) images is studied. We have developed a technique for smoothing these images by using a modified back projection filter with attenuated high frequency response. The results are images with a blurred appearance but dramatically reduced image noise. On processing raw data from the EMI head scanner in this way, grey and white matter distributions are clearly visualized with no increase in radiation dose. These results are analyzed in terms of the Weiner spectrum and correlation properties of CT noise. In particular, a "noise equivalent aperture" is defined in a way analogous to that of Shade. It is shown that the prediction of the simple Rose model of noise sampling can not explain the improvement produced by smoothing, even when the correlated character of the noise is taken into account.

Image Noise and Smoothing in Computed Tomography (CT) Scanners

The effects of image background on velocity computation of moving objects

Research was conducted to computer model and compare the image reconstruction obtainable using Wiener filtering and unsharp masking. Wiener filtering and unsharp masking are techniques used to improve image quality and interpretation. It was demonstrated that far greater image restoration is obtained by Wiener filter than by unsharp masking because unsharp masking, unlike Wiener filtering, enhanced image noise along with the edges. A user friendly computer model, that may be used as a tutorial aid for Image Science students, incorporating Fast Fourier Transform (FFT) techniques was designed. Graphics allow the user to follow each stage of the image processing.

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Image reconstruction using Wiener filtering and unsharp masking: a computer model

The signal-dependence of photographic grain is easily demonstrated by studying the first order statistics (mean and variance) of the scattered light in a coherent optical spectrum analyzer. It is shown empirically and from simple theoretical considerations that the granularity of the photographic material can be determined using a coherent measurement and can be interpreted as an inverse signal to noise ratio. The traditional linear Fourier domain filter can be shown by simple considerations to be ill-suited for dealing with the signal-dependence of photographic grain.© (1978) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Studies Of Photographic Grain In A Coherent Optical System: Signal-Dependence And Its Implications

An image enhancement technique called "Noise Cheating" allows the detection of low contrast objects in a noisy background. This technique has been applied to imagery degraded by blur and by noise. The technique is reviewed in this paper, and the results of its application are compared to the results using Wiener filtering. Comparisons are made on both computer simulated and laboratory-generated imagery. The results indicate that subjectively preferable restorations are achieved by Wiener filtering when blur, rather than image noise, is the dominant degrading factor, while noise cheating produces preferable results when noise is predominant.© (1976) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A. Silvestri

Papers

Experiments in Digital Restoration of Defocused Grainy Photographs by Noise Cheating and Fourier Techniques