THE INFLUENCE OF ADJACENCY EFFECTS ON THE RESTORATION OF NOISY PHOTOGRAPHIC IMAGES

Abstract

The objective of this study was to enable the removal of developer depletion and diffusion effects (i.e., adjacency effects from noisy photographic images, thus, providing a potential for improvement in the reliability of restored object and aerial image estimates. The investigation was based on the use of a previously formulated image resortation model which characterized the exposure, latent image and development interactions of the photographic process in terms of statistical estimation theory. This study addressed the application and appropriate modification of the formulated model in the removal of adjacency effects from noisy images of selected line targets. Literature pertaining to the initial observations of adjacency effects, their recognition as a nonlinear chemical development effect and the pertinent models (forward) used to predict their effects was reviewed. This was followed with a review of the statistical restoration (inverse) model and its comparison to previously derived forward models. X-ray quanta exposures were then used to obtain noisy photographic images, free of optical scattering effects, for the purpose of empirically determining a chemical spread function to characterize chemical adjacency effects. Photographic images were obtained that contained lines of 0.010, 0.100 and 1.000 mm widths to enable comparison between the magnitude of the chemical spread function and the Eberhard effect. A segmented polynomial (cubic spline function) approach was used to calculate the chemical spread function. Separate light quanta exposures were used to obtain gross grain density sensitometric curves and noisy line images. The covering power relationship between mass of developed silver and diffuse density was empirically derived for Panatomic-X film processed without agitation in D-76 developer (diluted 1:1). Emperical verification of the statistical restoration model was achieved. Chemical adjacency effects were successfully removed from noisy line images using an appropriately scaled version of the statistical restoration model. The spatial frequency content of the noisy line images was approximately 1, 10, 15, 20, 25 and 40 cycles/mm. The proportionality factor, used to scale the chemical spread function required in the restoration model, was found to be equivalent to the ratio of the empirically derived chemical spread function and a magnitude estimate of the Eberhard effect. The maximum diffuse density correction for edge effects was found to be 0.14, or approximately 11.1% of the gross grain density level, 1.20. Similar diffuse density corrections for fine line images were found to range between 0.14 and 0.36, or approximately 11.1% to 28.3% of the gross grain density level associated with a specific line element.