System and method for selecting a color space using a neural network
US5808621A · kind A · utility
Assignee
Inventor
Key dates
| Filing date | Apr 30, 1996 |
| Grant date | Sep 15, 1998 |
| Priority date | — |
| Expiry date | Apr 30, 2016 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T9/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for automatically selecting a color space for use in compressing and decompressing a texture image that automatically determines a compression color space for each texture image. The invention selects a compression color space manually, or preferable, using a neural network algorithm. The invention initializes the neural network that includes an input layer of neurons and a hidden layer of neurons. Each input layer neuron has an associated weight that is equal to the combination of the weights of a Y neuron, an A neuron, and a B neuron that is associated with each input layer neuron. The texel image is reduced into a representative sample of colors and input vectors from the texel image are randomly selected. For each input vector, the invention determines the two input layer neurons that most closely match the input vector and modifies the weights of the two input layer neurons to more closely match the value of the input vector. The weights of the hidden layer neurons represent the Y, A, and B-channel values of the optimal compression color space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.