Optimization and Regularization for Computational Inverse Problems and Applications : [papers presented by invited speakers of the first international workshop “Optimization and Regularization for Computational Inverse Problems and Applications”. The workshop was organized under the auspices of the Chinese Academy of Sciences in the Institute of Geology and Geophysics located in Beijing the capital of China and held during July 21–25 2008] Optimization and Regularization for Computational Inverse Problems and Applications focuses on advances in inversion theory and recent developments with practical applications particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods including standard regularization theory Fejer processes for linear and nonlinear problems the balancing principle extrapolated regularization nonstandard regularization nonlinear gradient method the nonmonotone gradient method subspace method and Lie group method and the practical applications such as the reconstruction problem for inverse scattering molecular spectra data processing quantitative remote sensing inversion seismic inversion using the Lie group method and the gravitational lensing problem. Scientists researchers and engineers as well as graduate students engaged in applied mathematics engineering geophysics medical science image processing remote sensing and atmospheric science will benefit from this book. Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics Chinese Academy of Sciences China. Dr. Sc. Anatoly G. Yagola is a Professor and Assistant Dean of the Physical Faculty Lomonosov Moscow State University Russia. Dr. Changchun Yang is a Professor and Vice Director of the Institute of Geology and Geophysics Chinese Academy of Sciences China.