Image De-blurring and Supper-Resolution by Adaptive Sparse Domain Selection and Regularization
نویسندگان
چکیده
منابع مشابه
Adaptive Frequency-domain Regularization for Sparse-data Tomography
A novel reconstruction technique, called Wiener Filtered Reconstruction Technique (WIRT), for sparse-data tomographic imaging is introduced. This six-step method applies a spatially varying constrained leastsquares filter combined with a regularization method based on total variation. The WIRT reconstruction is implemented in the frequency domain, where the information based on measurements and...
متن کاملCT Image Reconstruction from Sparse Projections Using Adaptive TpV Regularization
Radiation dose reduction without losing CT image quality has been an increasing concern. Reducing the number of X-ray projections to reconstruct CT images, which is also called sparse-projection reconstruction, can potentially avoid excessive dose delivered to patients in CT examination. To overcome the disadvantages of total variation (TV) minimization method, in this work we introduce a novel...
متن کاملOut-of-focus Blur: Image De-blurring
Image de-blurring is important in many cases of imaging a real scene or object by a camera. This project focuses on de-blurring an image distorted by an out-of-focus blur through a simulation study. A pseudo-inverse filter is first explored but it fails because of severe noise amplification. Then Tikhonov regularization methods are employed, which produce greatly improved results compared to th...
متن کاملStudy of Supper Resolution Processing Methods for Thick Pinhole Image
An image super resolution reconstruction method was used to improve the spatial resolution of the thick pinhole imaging system and to mitigate the limitations of the image spatial resolution of the hardware of the image diagnostic system. The thick pinhole is usually applied into the diagnostics of the high energy neutron radiation image. Due to the impacts among its energy flux, spatial resolu...
متن کاملWavelet domain image restoration with adaptive edge-preserving regularization
In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2016
ISSN: 0975-8887
DOI: 10.5120/ijca2016909645