Compressed sensing(CS) which serves as an alternative to Nyquist sampling theory, is being used in many areas of applications. In this paper, we applied recent compressed sensing algorithm such as DALM, FISTA and Split-Bregman on astronomical images. In astronomy, physical prior information is very crucial for devising effective signal processing methods. We particularly point out that CS-based compression scheme is flexible enough to account for such information. We try to compare these algorithms using objective measures like PSNR, MSE et al. With these measures we intend to verify the image quality of reconstructed and original images. © 2012 Springer-Verlag.
cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@30a68e6b ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@6d02bc1 Through org.apache.xalan.xsltc.dom.DOMAdapter@4ce88f65; Conference Code:92037
T. VaNidhin Prabhakar, Hemanth, V. Ka, Kumar, SaSachin, Soman, K. Pa, and Soman, Ab, “Comparative study of recent compressed sensing methodologies in astronomical images”, Communications in Computer and Information Science, vol. 305 CCIS. Kochi, pp. 108-116, 2012.