Application of Gabor Wavelet in Quantum Holography for Image Recognition

Gabor wavelet is considered the best mathematical descriptor for receptive fields in the striate cortex. As a basis function, it is suitable to sparsely represent natural scenes due to its property in maximizing information. It is argued that Gabor-like receptive fields emerged by the sparseness-enforcing or infomax method, with sparseness-enforcing being more biologically plausible. This paper incorporates Gabor over-complete representation into Quantum Holography for image recognition tasks. Correlations are performed using sampled result from all frequencies as well as the optimum frequency. Correlation is also performed using only those points of least activity, which shows improvements in recognition. Analysis on the use of conjugation in reconstruction is provided. The authors also suggest improvements through iterative methods for reconstruction.