Evolution of Wavelets and Hardware for Satellite Image Compression¶

When designing a system to transmit satellite images, it is important to balance the need for a high compression rate with the ability to accurately reconstruct them. The discrete wavelet transform (DWT) can be used to compress images and can be fine-tuned for specific classes of images, but it requires substantial hardware resources to perform floating-point multiplications. Separate research efforts to evolve wavelets and hardware multipliers have been performed, but not together. This work explores the use of several evolutionary and coevolutionary algorithms to address this gap, focusing on different ways of combining wavelets and hardware. The first algorithm evolves them in two separate stages, a second evolves them in pairs, and the third algorithm cooperatively coevolves two populations of wavelets and hardware. The results indicate that problem decomposition is most beneficial when evolution allows the components to interact during the search process.