| Abstract: | A method for a reversible transform between an image and image autocorrelation function has been devised, and it has been applied to the reduction of random noise in a microscope image. Object-related features of an image signal as well as noise features are overlapped at the vicinity of the origin of an image autocorrelation, and a peak is formed at this position. The present method removes the noise contribution in this peak and returns the autocorrelation function, thus corrected, to the image. An autocorrelation function is computed by two Fourier transforms as based on the convolution theorem. The inverse transform from the image autocorrelation function is made possible by performing two Fourier transforms in reverse to the above. This method has been developed to remove random noise more accurately from a single image (especially for nonperiodic images) than other image-processing methods such as smoothing techniques and low pass filtering. |
