چکیده مقاله
Compressive sensing CS is a new method for image sampling in contrast with well known Nyquist sampling theorem Sampling domain and sparse domain play important rule for perfect signal recovery in CS framework In this paper, the performance of four recovery algorithms are compared according to visualevaluation and an image assessment parameter where noiselet and Gaussian used as the sampling domain and Fourier transform FT , discrete Cosine transform DCT and Haar wavelet transform WT used as the sparse domain Furthermore, for synthetic aperture radar SAR images, using noiselet and Gaussian are also evaluated Due to the big size of SAR images and high computational expenses, the block based adaptive sampling based on edge detection is used
کلیدواژهها
نویسندگان
Haybert Markarian
Electrical and Electronic Engineering Department, Islamic Azad University Tehran South Branch, Tehran, Iran
Sedigheh Ghofrani
Electrical and Electronic Engineering Department, Islamic Azad University Tehran South Branch, Tehran, Iran
شیوه ارجاع
Markarian, Haybert and Ghofrani, Sedigheh,1394,Block Based Compressive Sensing for SAR Images by using Noiselet and Haar Wavelet,International Conference on New Research Findings in Electrical Engineering and Computer Science,Tehran
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