title: Medical image processing using novel wavelet filters based on atomic functions: optimal medical image compression.
abstract: The analysis of different Wavelets including novel Wavelet families based on atomic functions are presented, especially for ultrasound (US) and mammography (MG) images compression. This way we are able to determine with what type of filters Wavelet works better in compression of such images. Key properties: Frequency response, approximation order, projection cosine, and Riesz bounds were determined and compared for the classic Wavelets W9/7 used in standard JPEG2000, Daubechies8, Symlet8, as well as for the complex Kravchenko-Rvachev Wavelets ψ(t) based on the atomic functions up(t),  fup (2)(t), and eup(t). The comparison results show significantly better performance of novel Wavelets that is justified by experiments and in study of key properties.
authors: Autonomous University of Mexico State, Hermenegildo Galena No. 3, Col. Ma. Isabel, Valle de Chalco, Mexico State, Mexico. cjlandin@yahoo.com.mx
authors: Cristina Juarez
authors: CJ
authors: Landin
authors: Magally Martinez
authors: MM
authors: Reyes
authors: Anabelem Soberanes
authors: AS
authors: Martin
authors: Rosa Maria Valdovinos
authors: RM
authors: Rosas
authors: Jose Luis Sanchez
authors: JL
authors: Ramirez
authors: Volodymyr
authors: V
authors: Ponomaryov
authors: Maria Dolores Torres
authors: MD
authors: Soto
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D044962:Data Compression / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008327:Mammography / Q000706:statistics & numerical data; D014463:Ultrasonography / Q000706:statistics & numerical data