High-resolution images from low-resolution compressed video

Segall, C.A.; Molina, Rafael; Katsaggelos, Aggelos K.

doi:10.1109/msp.2003.1203208

Cited by 93 publications

(56 citation statements)

References 35 publications

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“…3. Visual results using increasing number of frames (1,5,9,13) from the 64x64 video sequence. Top left: the LR image.…”

Section: Lr 64x64mentioning

confidence: 99%

“…Several efficient solutions of the super-resolution problem have been proposed for images from perspective cameras [1,2,3]. In these cases, the related ill-posed inverse problem is formulated as a minimization regularized problem in which the regularization term is based on a Total Variation (TV) prior or a Tikhonov prior (using a classical 2 norm).…”

Section: Introductionmentioning

confidence: 99%

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Plenoptic based super-resolution for omnidirectional image sequences

Bagnato¹,

Boursier

Frossard³

2010

2010 IEEE International Conference on Image Processing

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This paper addresses the reconstruction of high resolution omnidirectional images from a low resolution video acquired by an omnidirectional camera moving in a static scene. In order to exploit the additional information provided by the side images in the video sequence, the ego-motion of the camera must be accurately estimated in a first step. The reconstruction can then be modeled as a plenoptic sampling problem that has to encompass the change of viewpoint between each position of the omnidirectional sensor and the specific discretization of the real scene observed from each position. We formulate this problem as an ill-posed inverse problem that incorporates a regularization term based on a Total Variation (TV) prior. A graph variational formulation is used in order to ease the representation of omnidirectional data and to adapt the discretization of differential operators to the omnidirectional geometry. Experimental results on synthetic images demonstrate the relevance of this approach and its superiority compared to standard super-resolution using a single image.

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“…3. Visual results using increasing number of frames (1,5,9,13) from the 64x64 video sequence. Top left: the LR image.…”

Section: Lr 64x64mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Plenoptic based super-resolution for omnidirectional image sequences

Bagnato¹,

Boursier

Frossard³

2010

2010 IEEE International Conference on Image Processing

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show abstract

“…This problem has been previously treated in the literature [18][19][20][21][22][23][24][25][26][27][28][29]. The first treatment to the supper resolution reconstruction problem was an iterative frequency domain treatment since the Fourier transform has superior properties for translational shifts between observations [18][19][20].…”

Section: Super-resolution Reconstruction Of Imagesmentioning

confidence: 99%

“…These algorithms aim at reducing the computational cost of the matrix inversion processes involved in the solution by using successive approximation methods for the estimation of the HR image. Most of the previously suggested solutions to this problem are based on the regularization theory [18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Super-resolution Reconstruction Of Imagesmentioning

confidence: 99%

“…Image interpolation is the process by which a single HR image can be obtained from a single degraded LR one [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17], while super-resolution reconstruction of images aims at obtaining a single HR image either from several degraded still images or from several degraded multiframes [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. This paper introduces a group of image interpolation and image super-resolution algorithms and some comparisons between them.…”

Section: Introductionmentioning

confidence: 99%

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New Techniques to Conquer the Image Resolution Enhancement Problem

El‐Khamy¹,

Hadhoud²,

Dessouky³

et al. 2008

PIER B

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Abstract-This paper presents some new techniques for high resolution (HR) image processing and compares between them. The paper focuses on two main topics, image interpolation and image superresolution. By image interpolation, we mean extracting an HR image from a single Degraded low resolution (LR) image. Polynomial based image interpolation is reviewed. Some new techniques for adaptive image interpolation and inverse image interpolation are presented. The other topic treated in this paper is image super-resolution. By image super resolution, we mean extracting a single HR image either from multiple observations or multiple frames. The paper focuses on the problem of image super resolution using wavelet fusion and presents several super resolution reconstruction algorithms based on the idea of wavelet fusion.

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High‐resolution images from compressed low‐resolution video: Motion estimation and observable pixels

Álvarez

Mateos

Molina

et al. 2004

Int J Imaging Syst Tech

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ABSTRACT:In this article, we address the problem of obtaining a high-resolution (HR) image from a compressed low-resolution (LR) video sequence. Motion information plays a critical role in solving this problem, and we determine which pixels in the sequence provide useful information for calculating the high-resolution image. The bit stream of hybrid motion compensated video compression methods includes low-resolution motion-compensated images; we therefore also study which pixels in these images should be used to increase the quality of the reconstructed image. Once the useful (observable) pixels in the low-resolution and motion-compensated sequences have been detected, we modify the acquisition model to only account for these observations. The proposed approach is tested on real compressed video sequences and the improved performance is reported.

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High-resolution images from low-resolution compressed video

Cited by 93 publications

References 35 publications

Plenoptic based super-resolution for omnidirectional image sequences

Plenoptic based super-resolution for omnidirectional image sequences

New Techniques to Conquer the Image Resolution Enhancement Problem

High‐resolution images from compressed low‐resolution video: Motion estimation and observable pixels

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