Single image Super Resolution by no-reference image quality index optimization in PCA subspace

Brian Sumali; Haslina Sarkan; Nozomu Hamada; Yasue Mitsukura

doi:10.1109/CSPA.2016.7515828

Single image Super Resolution by no-reference image quality index optimization in PCA subspace

Brian Sumali, Haslina Sarkan, Nozomu Hamada, Yasue Mitsukura

Department of System Design Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Principal Component Analysis (PCA) has been effectively applied for solving atmospheric-turbulence degraded images. PCA-based approaches improve the image quality by adding high-frequency components extracted using PCA to the blurred image. The PCA-based restoration process is similar with conventional single-frame Super-Resolution (SR) methods, which perform SR process by improving the edges portion of low-resolution images. This paper aims to introduce PCA-based restoration to solve SR problem with additive white Gaussian noise. We conducted experiments using standard image database and show comparative result with the latest deep-learning SR approach.

Original language	English
Title of host publication	Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	183-187
Number of pages	5
ISBN (Electronic)	9781467387804
DOIs	https://doi.org/10.1109/CSPA.2016.7515828
Publication status	Published - 2016 Jul 18
Event	12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016 - Melaka, Malaysia Duration: 2016 Mar 4 → 2016 Mar 6

Publication series

Name	Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016

Other

Other	12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016
Country/Territory	Malaysia
City	Melaka
Period	16/3/4 → 16/3/6

Keywords

Image Quality Assessment
Noise Robustness
Principal Component Analysis
Single Image
Super Resolution

ASJC Scopus subject areas

Signal Processing
Control and Systems Engineering
Control and Optimization

Access to Document

10.1109/CSPA.2016.7515828

Cite this

Sumali, B., Sarkan, H., Hamada, N., & Mitsukura, Y. (2016). Single image Super Resolution by no-reference image quality index optimization in PCA subspace. In Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016 (pp. 183-187). Article 7515828 (Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSPA.2016.7515828

Single image Super Resolution by no-reference image quality index optimization in PCA subspace. / Sumali, Brian; Sarkan, Haslina; Hamada, Nozomu et al.
Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 183-187 7515828 (Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sumali, B, Sarkan, H, Hamada, N & Mitsukura, Y 2016, Single image Super Resolution by no-reference image quality index optimization in PCA subspace. in Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016., 7515828, Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016, Institute of Electrical and Electronics Engineers Inc., pp. 183-187, 12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016, Melaka, Malaysia, 16/3/4. https://doi.org/10.1109/CSPA.2016.7515828

Sumali B, Sarkan H, Hamada N, Mitsukura Y. Single image Super Resolution by no-reference image quality index optimization in PCA subspace. In Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 183-187. 7515828. (Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016). doi: 10.1109/CSPA.2016.7515828

Sumali, Brian ; Sarkan, Haslina ; Hamada, Nozomu et al. / Single image Super Resolution by no-reference image quality index optimization in PCA subspace. Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 183-187 (Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016).

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abstract = "Principal Component Analysis (PCA) has been effectively applied for solving atmospheric-turbulence degraded images. PCA-based approaches improve the image quality by adding high-frequency components extracted using PCA to the blurred image. The PCA-based restoration process is similar with conventional single-frame Super-Resolution (SR) methods, which perform SR process by improving the edges portion of low-resolution images. This paper aims to introduce PCA-based restoration to solve SR problem with additive white Gaussian noise. We conducted experiments using standard image database and show comparative result with the latest deep-learning SR approach.",

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Single image Super Resolution by no-reference image quality index optimization in PCA subspace

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