We present a method to find the mean square estimate of the original image using a Gauss-Markov image model and a known point spread function. The performance of the edge adaptive technique compares favorably to the Wiener filter on synthetic and real images with mild linear (motion) blur and additive white Gaussian noise.

A fundamental question for edge detection is how faint an edge can be and still be detected. In this paper we offer a formalism to study this question and subsequently introduce a hierarchical edge detection algorithm designed to detect faint curved edges in noisy images. In our formalism we view edge detection as a search in a space of feasible curves, and derive expressions to characterize th...

We propose a variational model which permits to simultaneously deblur and oversample an image. Indeed, after some recalls on an existing variational model for image oversampling, we show how to modify it in order to properly achieve our two goals. We discuss the modification both under a theoretical point of view (the analysis of the preservation of some structural elements) and the practical p...

Multiscale image registration techniques are presented for the registration of medical images using deformable registration models. The techniques are particularly effective for registration problems in which one or both of the images to be registered contains significant levels of noise. A brief overview of existing deformable registration techniques is presented, and experiments using B-splin...

This paper presents a technique for deblurring noisy images. It includes two processing blocks, one for denoising and another for blind image restoration. The denoising step is based on the theories of singular value decomposition and compression-based filtering. The deblurring step is based on a double-regularization technique. Experimental results show that the combination of these techniques...

How should one filter very noisy images of curves? While blurring with a Gaussian reduces noise, it also reduces contour contrast. Both non-homogeneous and anisotropic diffusion smooth images while preserving contours, but these methods assume a single local orientation and therefore they can merge or distort nearby or crossing contours. To avoid these difficulties, we view curve enhancement as...

Detecting spatial regularity in images arises in computer vision, scene analysis, military applications, and other areas. In this paper we present an O(n 5 2 ) algorithm that reports all maximal equally-spaced collinear subsets. The algorithm is robust in that it can tolerate noise or imprecision that may be inherent in the measuring process, where the error threshold is a user-speci ed paramet...

This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have...

In this paper, we propose to study the problem of noisy source coding/denoising. The challenge of this problem is that a global optimization is usually difficult to perform as the global fidelity criterion needs to be optimized in the same time over the sets of both coding and denoising parameters. Most of the bibliography in this domain is based on the fact that, for a specific criterion, the ...

The spatial and scale space domain techniques are used independently to detect edges of the noisy images. When noise density surpasses a limit, classical operators are unable to detect the edges. The frequency domain filtering for edge detection in a noisy scenario is inadequate due to Fourier’s global behavior. Wavelet analysis for noisy images also reveals dominance of noisy pixels over the e...