Image Compression by Orthogonal Decomposition and Dynamic Segmentation Using Cellular Nonlinear Network
Tamh Snkinp · 1998
In this paper a new method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimensional (20) orthogonal transformations. Using these 2D basisfitnctions of the Hadamard or Cosine finctions, the transformation coefficients of the basic blocks of the image are measured by the ChW. Meanwhile, the CNN can produce the inverse transformation of the measured coeflcients and the actual distortion-rate can be computed. If a required distortion-rate is reached, the coding process could be stopped (the use of even more coefficients would increase bit-rate needlmsly). Efects of noise and VLSI computing accuracy are also considered to optimise the architecture. Here we also give a short description how to join the transform coding method and the object-oriented image model.