References Image Compression by Edge Pattern Learning Using Multilayer P Erc E Ptro N S
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Improved neural structures for image compression
The problem considered is the effective compression of image data. Compared to the many methods which allow for high compression factors (mainly based on the DCT), the proposed neural approaches offer, after a suitable training, comparable performance both in terms of perceived image quality and measured SNR. Moreover, they are able to perform in the same step the two main required operations of transformation and selection of the most significant terms, with a correspondingly smaller computational effort.<<ETX>>
Artificial neural network for image compression
An artificial neural network is proposed which is able to compress an image by computing a nonlinear nonorthogonal transform and its inverse. The network is trained with small blocks extracted from an image; after the learning phase, it proves to give satisfactory performances both for the learned and for different unlearned images.