Image association using a Complex-Valued Associative Memory Model
This paper presents an application of Complex Valued Associative Memory Model(CAMM) for image processing. An image association system applying CAMM I, combined with a 2-dimensional discrete Fourier transform (2-D DFT) process is proposed. Discussed are how a gray level image can be expressed using CAMM, and the image association that can be performed by CAMM. In the proposed system, input images are transformed to phase matrices and the image association can be performed-by making use of the phase information. Practical examples are also presented.
complex-valued associative memory discrete fourier transform gray level image muiti-valued neuron