On compressed sensing and super-resolution in DFT-based spectral analysis
نویسندگان
چکیده
Abstrac t -The paper discusses a novel frequency interpolation and super-resolution method for multitone waveform analysis, where a compressive sensing algorithm is employed to process data. Each signal acquisition involves a short data record, whose DFT coefficients are computed. A set of compressed measurements is obtained by taking records with different known starting instants, and employed to determine, by solving an orthogonal matching pursuit problem, the set of frequency components of the analysed waveform. Interpolation is presented as a compressed sensing problem and algorithm performances discussed.
منابع مشابه
Super-resolution of Hyperspectral Images Using Compressive Sensing Based Approach
Over the past decade hyper spectral (HS) image analysis has turned into one of the most powerful and growing technologies in the field of remote sensing. While HS images cover large area at fine spectral resolution, their spatial resolutions are often too coarse for the use in various applications. Hence improving their resolution has a high payoff. This paper presents a novel approach for supe...
متن کاملObject Level Strategy for Spectral Quality Assessment of High Resolution Pan-sharpen Images
Panchromatic and multi-spectral images produced by the remote sensing satellites are fused together to provide a multi-spectral image with a high spatial resolution at the same time. The spectral quality of the fused images is very important because the quality of a large number of remote sensing products depends on it. Due to the importance of the spectral quality of the fused images, its eval...
متن کاملHigh Resolution Spectral Estimation using BP via Compressive Sensing
In this paper we propose a method based on compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of sinusoids. In the case of finite-length signals, the Fourier coefficients are not exactly sparse due to the leakage effect if the frequency is not a multiple of the fundamental frequency; To overcome this problem our algorithm transform ...
متن کاملStudy on the Super-resolution Reconstruction Algorithm for Remote Sensing Image Based on Compressed Sensing
Image super resolution reconstruction has important significance in remote sensing image feature extraction and classification etc.. Because the remote sensing image size is larger, it is difficult to super resolution reconstruction using multiple images, the compressed sensing (CS) theory was introduced into the super-resolution reconstruction. Algorithm designed the low pass filter to reduce ...
متن کاملSuper-Resolution Compressed Sensing: A Generalized Iterative Reweighted L2 Approach
Conventional compressed sensing theory assumes signals have sparse representations in a known, finite dictionary. Nevertheless, in many practical applications such as directionof-arrival (DOA) estimation and line spectral estimation, the sparsifying dictionary is usually characterized by a set of unknown parameters in a continuous domain. To apply the conventional compressed sensing technique t...
متن کامل