Estimation of noise component in satellite images and its application

The median filter is known to be effective to estimate the amount of noise present in the image. The authors investigate its performance quantitatively, and it is compared with the Laplacian filter and the trimmed mean filter. The estimated variances are adjusted to give an unbiased estimate under ideal conditions with no structure in the image. It is also shown that the trimmed mean filter as well as the median filter are robust to simple line edge structures. The author also discusses the estimation of the covariance matrix of the noise component with interband correlation, which is useful in many algorithms for image processing, such as edge detection, data compression, and image enhancement.