Phase Based Image Reconstruction in the Monogenic Scale Space

نویسندگان

  • Di Zang
  • Gerald Sommer
چکیده

In this paper, we present an approach for image reconstruction from local phase vectors in the monogenic scale space. The local phase vector contains not only the local phase but also the local orientation of the original signal, which enables the simultaneous estimation of the structural and geometric information. Consequently, the local phase vector preserves a lot of important information of the original signal. Image reconstruction from the local phase vectors can be easily and quickly implemented in the monogenic scale space by a coarse to fine way. Experimental results illustrate that an image can be accurately reconstructed based on the local phase vector. In contrast to the reconstruction from zero crossings, our approach is proved to be stable. Due to the local orientation adaptivity of the local phase vector, the presented approach gives a better result when compared with that of the Gabor phase based reconstruction.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

A stereo similarity function based on local multi-model monogenic image feature descriptors LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color...

متن کامل

GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives

In this paper we propose a new operator which combines advantages of monogenic scale-space and Gaussian scale-space, of the monogenic signal and the structure tensor. The gradient energy tensor (GET) defined in this paper is based on Gaussian derivatives up to third order using different scales. These filters are commonly available, separable, and have an optimal uncertainty. The response of th...

متن کامل

Fast Reconstruction of SAR Images with Phase Error Using Sparse Representation

In the past years, a number of algorithms have been introduced for synthesis aperture radar (SAR) imaging. However, they all suffer from the same problem: The data size to process is considerably large. In recent years, compressive sensing and sparse representation of the signal in SAR has gained a significant research interest. This method offers the advantage of reducing the sampling rate, bu...

متن کامل

Monogenic Scale Space Based Region Covariance Matrix Descriptor for Face Recognition

In this paper, we have presented a new face recognition algorithm based on region covariance matrix (RCM) descriptor computed in monogenic scale space. In the proposed model, energy information obtained using monogenic filter is used to represent a pixel at different scales to form region covariance matrix descriptor for each face image during training phase. An eigenvalue based distance measur...

متن کامل

INSTITUT FÜR INFORMATIK A Novel Representation for Two-dimensional Image Structures

This paper presents a novel approach towards two-dimensional (2D) image structures modeling. To obtain more degrees of freedom, a 2D image signal is embedded into a certain geometric algebra. Coupling methods of differential geometry, tensor algebra, monogenic signal and quadrature filter, we can design a general model for 2D structures as the monogenic extension of a curvature tensor. Based on...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004