Optimal log-polar image sampling

In order to achieve better image compression simultaneously maintaining the high signal quality, the image sampling has become very important. Also, since the human eye sensitivity has circularly symmetric distribution, in recent years it is usual to apply log-polar image sampling. In this paper, we perform optimization of log-polar image sampling and show the significant improvement in comparison with the product log-polar sampling. Namely, for equal numbers of sensors optimal model gives higher signal-to-noise ratio (SNR) up to 2.5 dB, i.e., it is possible to decrease the number of required sensors by 45% for the same SNR. Furthermore, research shows that in optimal log-polar image sampling, the middle region of image, which is not sampled, can be made to be smaller than in the case of product sampling.