Image compression and SANN equations

Ying Liu

doi:10.1117/12.152561

2 September 1993 Image compression and SANN equations

Ying Liu

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152561
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Image compression can be achieved by using stochastic artificial neural networks (SANN). The idea is to store an image in stable distribution of a stochastic neural network. Given an input image f (epsilon) F, one can find a SANN t (epsilon) T such that the equilibrium distribution this SANN is the given image f. Therefore, the input image, f, is encoded into a specification of a SANN, t. This mapping from F (image space) to T (parameter space of SANN) defines SANN transformation. To complete a SANN transformation, an SANN equation has to be solved. In this paper, we will first introduce two types of SANN equations. Then, we will develop an algorithm to solve SANN equation.

Citation Download Citation

Ying Liu "Image compression and SANN equations", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152561

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