almansa's super-resolution [8 articles]

Abstract

This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This non-local graph allows to adapt the penalization to the geometry of the underlying function to recover. A fast algorithm computes iteratively both the solution of the regularization process and the non-local graph adapted to this solution. We show numerical applications of this method to the resolution of image processing inverse problems such as inpainting, super-resolution and compressive sampling. ...

Abstract

Abstract  In this paper we formulate a new time dependent convolutional model for super-resolution based on a constrained variational model that uses the total variation of the signal as a regularizing functional. We propose an iterative refinement procedure based on Bregman iteration to improve spatial resolution. The model uses a dataset of low resolution images and incorporates a downsampling operator to relate the high resolution scale to the low resolution one. We present an algorithm for the model and we perform a ...

Abstract

The attainment of super resolution (SR) from a sequence of degraded undersampled images could be viewed as reconstruction of the high-resolution (HR) image from a finite set of its projections on a sampling lattice. This can then be formulated as an optimization problem whose solution is obtained by minimizing a cost function. The approaches adopted and their analysis to solve the formulated optimization problem are crucial, The image acquisition scheme is important in the modeling of the degradation process. The need ...

Abstract

High resolution remote sensing optical systems which are based upon the push-broom acquisition principle, have usually a significant Modulation Transfer Function (MTF) value at Nyquist frequency which leads to aliasing and sub optimization of the system: the sampling grid is not dense enough to catch all the spatial frequencies transmitted through the optics and the CCD. This papers analyses the image acquisition process from a signal processing point of view by reducing it to a three component set: MTF, signal to ...

Abstract

Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasing) are introduced in the image, the good side is that images can be improved if the sampling density is increased. In this paper we use images from the two HRVIR instruments onboard SPOT1-4 satellite to multiply by a factor two the density and the ...

Abstract

In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the A/D converter, etc. A low-pass filter is then often applied before the sampling operation to avoid aliasing. However, when multiple copies are available, it is possible to use the information that is inherently present in the aliasing to reconstruct a higher resolution signal. If the different copies have unknown relative offsets, this is a non-linear problem in the offsets ...

Abstract

Aliasing in images is often considered as a nuisance. Artificial low frequency patterns and jagged edges appear when an image is sampled at a too low frequency. However, aliasing also conveys useful information about the high frequency content of the image, which is exploited in super-resolution applications. We use a set of input images of the same scene to extract such high frequency information and create a higher resolution aliasing-free image. Typically, there is a small shift or more complex motion ...