CS image reconstruction by novel small length LDPC code
Tóm tắt
Compressed sensing (CS) is capable of reconstructing the data signal from very small number of measurements. However the reconstructed image quality gets highly affected in the case of far end reconstruction involving transmission through a channel. In this work, a novel small length binary low density parity check (LDPC) code for far-end transmission of compressively sampled signals is proposed. Smaller length of LDPC code means faster computation. Also the code rate of proposed LDPC code is constructed to be 0.6 as in an earlier work by the same group it has been demonstrated that quasi-cyclic LDPC codes, with code rate 0.67 gives optimum performance with CS. The proposed code has a base matrix of size 4 × 10. The length of the LDPC code constructed, can be adjusted by a base matrix multiplying factor. The multiplying factor varies from 10 to 30 in steps of 4. The constructed code has a variable length between 100 and 300, in steps of 40. Simulation results of the proposed LDPC code show good performance when decoded iteratively by min-sum decoding algorithm. The proposed LDPC code also gives improved CS reconstruction for far end reconstruction.
Tài liệu tham khảo
Zhang Y (2008) Theory of compressive sensing via 1-minimization: a non-RIP analysis and extensions. Ph.D. thesis, Department of Computational and Applied Mathematics, Rice University, Houston, TX, Tech. Rep. TR08-11 (revised)
Chen SS, Donoho DL, Saunders MA (1998) Atomic decomposition by basis pursuit. SIAM J Sci Comput 20:33–61
Fowler JE, Mun S, Tramel EW (2011) Multiscale block compressed sensing with smoothed projected Landweber reconstruction. In: Proceedings of the european signal processing conference, pp 564–568
Candes EJ, Wakin MB (2008) An introduction to compressive sampling. IEEE Signal Process Mag 25(2):21–30
Tropp JA, Gilbert AC (2007) Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inf Theory 53(12):4655–4666
Pramanik A, Maity SP (2015) On CS Reconstruction images using LDPC code over radio mobile channel. In: Proceedings IEEE global wireless summit wireless vitae
Gallager RG (1963) Low-density parity-check codes. Ph.D. thesis, Department of Electrical Engineering, MIT Press, MIT, Cambridge, MA
Chung SY, Forney G, Richardson T, Urbanke R (2001) On the design of low-density parity-check codes within 0.0045 dB of the Shannon limit. IEEE Commun Lett 5(2):58–60
Lu W, Kpalma K, Ronsin J (2012) Sparse binary matrices of LDPC codes for compressed sensing. In: Data compression conference
Dimakis AG, Smarandache R, Vontobel PO (2012) LDPC Codes for Compressed Sensing. IEEE Trans Inf Theory 58(5):3093–3114
Chen F, Lim F, Abari O, Chandrakasan A, Stojanovi V (2013) Energy-aware design of compressed sensing systems for wireless sensors under performance and reliability constraints. IEEE Trans Circuits Syst I 60(3):650–661
Zorlein H, Lazich D, Bossert M (2011) Performance of error correction based on compressed sensing. In: International symposium on wireless communication systems, Aachen
Richardson TJ, Urbanke RL (2001) Efficient encoding of low-density parity-check codes. IEEE Trans Inf Theory 47(2):638–656
David MacKay, Inference Group. http://www.inference.phy.cam.ac.uk/mackay/codes/data.html#s32