Digitised pictures have both cosmetic and scientific image aspects. This thesis presents an image coding system that compresses monochromatic digital image information in such a way that the cosmetic-or viewed-image aspects of a reconstructed picture are indistinguishable from the original to a (human) observer. The coding system is concerned with viewed aspects of digitised images and is based on a simplified 2-channel model of the human eye, with the image information being separated into slowly varying texture information and rapidly changing edge information corresponding to those two channels. Each of the two types of image data is coded using techniques suited to its individual characteristics. Texture information is coded using predictive waveform coding where the predictive filter coefficients are generated by linear predictive coding (LPC) techniques. Since the waveform prediction is not perfect, this thesis evaluates several different methods of differential pulse code modulation (DPCM) coding the residual prediction error. This signal is then used to improve the texture coding quality. Image edges are isolated from the digital image data by an asymptotically optimal edge detector known as the Laplacian of Gaussian (LOG) filter. Using two image edge models, the LOG isolated edges produce contours which are used to define edge position, shape, and "sharpness". The edge position data is then compressed using a chain-coding system. The thesis also considers the effect the edge characteristics have on the coding system and develops two methods for reducing the number of coded edges. Reconstruction of the coded image is in two parts corresponding to the two channels of the coding system. The texture information is reconstructed by predicting texture pixels and adding the decoded DPCM error signal. Edge information not contained in the texture coding channel is reconstructed using only edge information corresponding to the high spatial frequency channels of the human eye. These two channels are added together producing the final coded image reconstruction. Also considered are the effects of varying the original image sampling density. The 2-channel coding system is applicable to a wide variety of images, producing coded images with a high visual quality and coding bitrates as low as 0.6 bits/pixel (256 x 256 pixel images), while maintaining a relatively low computational overhead both at the encoder and the decoder.
| Identifer | oai:union.ndltd.org:ADTP/247552 |
| Date | January 1990 |
| Creators | Knowles, David John |
| Publisher | ResearchSpace@Auckland |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated., http://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm, Copyright: The author |
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