منابع مشابه
Blind image deblurring via coupled sparse representation
The problem of blind image deblurring is more challenging than that of non-blind image deblurring, due to the lack of knowledge about the point spread function in the imaging process. In this paper, a learningbased method of estimating blur kernel under the ‘0 regularization sparsity constraint is proposed for blind image deblurring. Specifically, we model the patch-based matching between the b...
متن کاملImage Deblurring Via Total Variation Based Structured Sparse Model Selection
Retina imaging technology is an effective control method for early diagnosis and early treatment of the diabetic retinopathy. In this paper, a fast robust inverse diffusion equation combining a blockwise filtering is presented to detect and evaluate diabetic retinopathy using retinal image enhancement. A flux corrected transport technique is used to control diffusion flux adaptively, which elim...
متن کاملBlind Image Deblurring Using Row-Column Sparse Representations
Blind image deblurring is a particularly challenging inverse problem where the blur kernel is unknown and must be estimated en route to recover the deblurred image. The problem is of strong practical relevance since many imaging devices such as cellphone cameras, must rely on deblurring algorithms to yield satisfactory image quality. Despite significant research effort, handling large motions r...
متن کاملAdaptive deblurring of noisy images.
We propose a practical sensor deblurring filtering method for images that are contaminated with noise. A sensor blurring function is usually modeled via a Gaussian-like function having a bell shape. The straightforward inverse function results in the magnification of noise at high frequencies. To address this issue, we apply a special spectral window to the inverse blurring function. This speci...
متن کاملPartially Linear Estimation with Application to Image Deblurring Using Blurred/Noisy Image Pairs
We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum mean squared error (PLMMSE) estimator requires knowing only the second-order moments of X and Y , making it of potential interest in various applications. We demonstrate the utility of PLMMSE estimation in recovering a s...
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: IEEE Transactions on Image Processing
سال: 2012
ISSN: 1057-7149,1941-0042
DOI: 10.1109/tip.2011.2175934