Most relevant weighted filtering with one-step singular correlation recognition

摘要

Based on the recognition of one-step singular correlation and the remedying methods obtained before,the correlation properties of the neighborhood pixels and the characteristics of image de-noising were analyzed.A kind of most relevant weighted filtering method based on one-step singular correlation recognition(OSSC-MRWF)was put forward.The simulation experiments were done and the comparison with some commonly used methods under salt-and-pepper noises was made.The results show that the proposed method can not only effectively recognize salt-and-pepper noises and mend up the noise points,but also protect the original information such as the edge details very well.The accuracy and performance indicators are further improved considerably.