Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this p...Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this paper,a novel image distortion metric based on minimal Total Bounded Variation(TBV) is presented.It is clarified that when the restored image approximates to the original clear image,the smaller the TBV is,the better the definition of the restored image is.Furthermore,the difference between the restored image and the original clear image is the smallest when the TBV is minimum.In numerical results,the TBV of the original clear image,blur image and restored image are presented and compared,and the results demonstrate the validity of the distortion metric proposed.展开更多
Texture extract from digital aerial image is widely used in three-dimensional city modeling to generate “photo-realistic” views. In this paper, a method based on reforming “Steep edge” curve, which clearly explain...Texture extract from digital aerial image is widely used in three-dimensional city modeling to generate “photo-realistic” views. In this paper, a method based on reforming “Steep edge” curve, which clearly explains how the diffraction of the sunlight makes digital aerial image blurring, is proposed to deblur the texture extraction from digital aerial image, and the experiment shows a good result in visualization and automation.展开更多
Superresolution is an image processing technique that estimates an original high-resolutionimage from its low-resolution and degraded observations.In superresolution tasks,there have beenproblems regarding the computa...Superresolution is an image processing technique that estimates an original high-resolutionimage from its low-resolution and degraded observations.In superresolution tasks,there have beenproblems regarding the computational cost for the estimation of high-dimensional variables.Theseproblems are now being overcome by the recent development of fast computers and the developmentof powerful computational techniques such as variational Bayesian approximation.This paper reviewsa Bayesian treatment of the superresolution problem and presents its extensions based on hierarchicalmodeling by employing hidden variables.展开更多
基金supported by the Fund of National Science & Technology monumental projects under Grants No.2012ZX03005012,No. 2011ZX03005-004-03,No.2009ZX03003-007
文摘Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this paper,a novel image distortion metric based on minimal Total Bounded Variation(TBV) is presented.It is clarified that when the restored image approximates to the original clear image,the smaller the TBV is,the better the definition of the restored image is.Furthermore,the difference between the restored image and the original clear image is the smallest when the TBV is minimum.In numerical results,the TBV of the original clear image,blur image and restored image are presented and compared,and the results demonstrate the validity of the distortion metric proposed.
文摘Texture extract from digital aerial image is widely used in three-dimensional city modeling to generate “photo-realistic” views. In this paper, a method based on reforming “Steep edge” curve, which clearly explains how the diffraction of the sunlight makes digital aerial image blurring, is proposed to deblur the texture extraction from digital aerial image, and the experiment shows a good result in visualization and automation.
文摘Superresolution is an image processing technique that estimates an original high-resolutionimage from its low-resolution and degraded observations.In superresolution tasks,there have beenproblems regarding the computational cost for the estimation of high-dimensional variables.Theseproblems are now being overcome by the recent development of fast computers and the developmentof powerful computational techniques such as variational Bayesian approximation.This paper reviewsa Bayesian treatment of the superresolution problem and presents its extensions based on hierarchicalmodeling by employing hidden variables.
