TY - GEN
T1 - PSO ICA with BRM for image enhancement
AU - Lee, Shih Hsiung
AU - Yang, Chu Sing
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/16
Y1 - 2016/8/16
N2 - In the teletransmission of images or medical imaging, image reconstruction or enhancement (denoising) is a significant topic. We can consider it as a typical issue of the Blind Source Separation (BSS) which interfere with transmission and cause blurs in images. Denoising and reconstruction refer to the removal of the unknown signals which lead to interference from the signals we intend to receive. Independent component analysis (ICA) has prominent performance in this field. This paper proposed to apply particle swarm optimization (PSO) algorithm to conduct accelerated computing of the rate of convergence of demixing matrix in ICA. Besides, it used Borel Regular Measure (BRM) based on Infomax to put forward a simple algorithm which was potential to be realized on a circuit chip. Our results of experiment have proved that after the separation of noises, the PSNR of the images has an apparent good effect. In addition, in the era of the Internet of Things, image and video perceptive products are facing the noises generated in transmission or by hardware interference. This paper will serve as an effective solution.
AB - In the teletransmission of images or medical imaging, image reconstruction or enhancement (denoising) is a significant topic. We can consider it as a typical issue of the Blind Source Separation (BSS) which interfere with transmission and cause blurs in images. Denoising and reconstruction refer to the removal of the unknown signals which lead to interference from the signals we intend to receive. Independent component analysis (ICA) has prominent performance in this field. This paper proposed to apply particle swarm optimization (PSO) algorithm to conduct accelerated computing of the rate of convergence of demixing matrix in ICA. Besides, it used Borel Regular Measure (BRM) based on Infomax to put forward a simple algorithm which was potential to be realized on a circuit chip. Our results of experiment have proved that after the separation of noises, the PSNR of the images has an apparent good effect. In addition, in the era of the Internet of Things, image and video perceptive products are facing the noises generated in transmission or by hardware interference. This paper will serve as an effective solution.
UR - http://www.scopus.com/inward/record.url?scp=84986193626&partnerID=8YFLogxK
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U2 - 10.1109/IS3C.2016.87
DO - 10.1109/IS3C.2016.87
M3 - Conference contribution
AN - SCOPUS:84986193626
T3 - Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
SP - 307
EP - 310
BT - Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
Y2 - 4 July 2016 through 6 July 2016
ER -