A new method based on Spatial Dimension Correlation and Fast Fourier Transform for SNR estimation in remote sensing images

For optical remote sensing images which are contaminated by white Gaussian noise, in general, uniform features indicate the same spectral characteristic. Uniform features will present the same or similar digital number (DN) value with a certain band in imaging. Therefore, the DNs of the uniform features are highly correlated [1]. When dividing an image into small blocks to estimate noise standard-deviations (SDs) and distributing SDs into a number of bins with equal width, within the minimum to the maximum SD, the statistical curve of numbers of SDs in bins theoretically meets Gaussian distribution [2]. Combining the two features, we develop a new method for SNR estimation. Results of tests indicate the new method performs better than other ones and overcome some disadvantages of some typical methods.