Abstract
A new noise reduction method, which is named APR (Adaptive Peak Rejection) for MSS (Multi-Spectral Scanner) image data is developed. Although many of the signal components of image data are lost if they are processed by a spatial low pass filter or by a running mean method, the APR method loses very few signal components of the image data. For, the APR method uses the scan overlap positively, which has not been used in the usual methods.
And APR not only reduces as much random Gaussian noise as can be reduced by a running mean method using scan overlap but also rejects spiky noise almost perfectly. Moreover, APR does nothing on the image data which include no such noise, and has a simple algorithm. Thus it is concluded that APR method is most suitable to pre-process the MSS image data.
In this paper, the scan overlap and APR method are discussed. And the superiority of APR method to the running mean method using scan overlap is proved by means of actual MSS image data processing.
