Sparse and Compressive Sensing Techniques

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• ESEN YILDIRIM

The authors address the problem of reconstruction of a high-resolution image from a number of lower-resolution (possibly noisy) frames of the same scene where the successive frames are uniformly based versions of each other at subpixel displacements. In particular, two previously proposed methods, a frequency-domain m…

This article presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal representation formulations for SAR image formation together with the associated imaging results, 2) sparsity-based methods for wide-a…

• NAİME ÖZBEN ÖNHON

Purpose The manufacturing of intelligent and secure visual data transmission over the wireless sensor network is key requirement nowadays to many applications. The two-way transmission of image under a wireless channel needed image must compatible along channel characteristics such as band width, energy-efficient, tim…

• BİLAL ÖZTÜRK

The challenging task while transmitting the high-quality images over the wireless sensor networks is to achieve the higher throughput, minimum bit error rate without compromising the image quality. As the sensor nodes have the limited processing power, designing energy efficient image transmission is another challenge…

• HACI İLHAN

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• HACI İLHAN

The challenging task while transmitting the high-quality images over the wireless sensor networks is to achieve the higher throughput, minimum bit error rate without compromising the image quality. As the sensor nodes have the limited processing power, designing energy efficient image transmission is another challenge…

• BİLAL ÖZTÜRK

The compressed sensing (CS) paradigm unifies sensing and compression of sparse signals in a simple linear measurement step. Reconstruction of the signal from the CS measurements relies on the knowledge of the measurement matrix used for sensing. Generation of the pseudo-random sensing matrix utilizing a cryptographic…

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• ALİ ÇİVRİL

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic apertur…

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• BİLAL ÖZTÜRK

An optimal statistical parameter estimation technique is presented for the identification of unknown image and blur model parameters. The development leads to an autoregressive moving average (ARMA) model identification problem, where the image model coefficients define the AR part, and the blur parameters define the…

• AHMET MURAT TEKALP