Undecimated Wavelet Transforms for Image De-noising

Gyaourova, A ; Kamath, C ; Fodor, I K

Lawrence Livermore National Laboratory

关键词: Signal-To-Noise Ratio;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;    Algorithms;    Images;    Image Processing;   

DOI  :  10.2172/15002085
RP-ID  :  UCRL-ID-150931
RP-ID  :  W-7405-ENG-48
RP-ID  :  15002085

美国|英语

来源: UNT Digital Library

【 摘 要 】

A few different approaches exist for computing undecimated wavelet transform. In this work we construct three undecimated schemes and evaluate their performance for image noise reduction. We use standard wavelet based de-noising techniques and compare the performance of our algorithms with the original undecimated wavelet transform, as well as with the decimated wavelet transform. The experiments we have made show that our algorithms have better noise removal/blurring ratio.