An Extra-Rate Spatial Enhancement Constructed by MSRR using Regularized Technique and SSRR using High-Frequency Pre-Forecasting
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Abstract
Under many circumstances, a high spatial resolution image (HR) is greatly needed for modern applications nevertheless the HR image captured device is usually overpriced cost. Hence, Super Resolution Reconstruction (SRR) technique, which can reconstruct a HR image from a single LR image or many LR images by using algebraic formulation, is one of the modern research fields in digital image processing (DIP) and Computer Vision (CV). In this paper, an extra-rate spatial enhancement constructed by MSRR (Multi-frame Super Resolution Reconstruction) using regularized technique and SSRR (Single-frame Super Resolution Reconstruction) using high-frequency pre-forecasting is presented in order to enlarge up to 16x ratio rate. Initially, a group of captured images with low spatial resolution are mathematically fused by MSRR using regularized technique established on a recursive Maximum Likelihood and Tukey's Biweight norm in order to enlarge up to 4x ratio rate. Next, this 4x enhanced image is enlarged to be 16x spatial resolution image by SSRR established on the high-frequency pre-forecasting. In the verification experimentation section, the verification outcome demonstrates that the proposed spatial enhancement is successful for enlarging HR image with 16x ratio rate with finer quality.
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References
Bo-Won Jeon, Rae-Hong Park and Seungjoon Yang, “Resolution Enhancement by Prediction of the High-Frequency Image Based on the Laplacian Pyramid”, EURASIP JASP, Hindawi Publishing Corp. 2006.
D. Rajan et al., Multi-Objective Super Resolution Concepts and Examples, IEEE SP. Mag., May 2003.
Dirk Robinson and Peyman Milanfar, Statistical Performance Analysis of Super-Resolution, IEEE Trans. IP., Vol. 15, No. 6, June 2006.
P. J. Burt and E. H. Adelson, “The Laplacian pyramid as a compact image code,” IEEE Transactions on Communications, vol. 31, 1983.
R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall,Upper Saddle River,NJ, USA, 2nd edition, 2002.
Moon Gi Kang and Subhasis Chaudhuri, Super-Resolution Image Reconstruction, IEEE SP. Mag., vol. 20, May. 2003.
M. J. Black and A. Rangarajan, On The Unification Of Line Processes, Outlier Rejection and Robust Statistics with Applications in Early Vision, International Journal of Computer Vision 19, 1, Jul. 1996.
M. K. Ng and Nirmal K. Bose, Mathematical analysis of super-resolution methodology, IEEE SP. Mag., May. 2003.
S. C. Park et al., Super-Resolution Image Reconstruction : A Technical Overview, IEEE SP. Mag., May 2003.
V. Patanavijit and S. Jitapunkul, A Robust Iterative Multiframe Super-Resolution Reconstruction using a Bayesian Approach with Tukey’s Biweigth, Proceeding of IEEE International Conference on Signal Processing 2006 (ICSP 2006), Guilin, China, Nov. 2006.
Vorapoj Patanavijit, Super-Resolution Reconstruction and its Future Research Direction, AU Journal of Technology (AU J.T.), Assumption University, Thailand, Jan. 2009.
Vorapoj Patanavijit, Mathematical Analysis of Stochastic Regularization Approach for Super-Resolution Reconstruction, AU Journal of Technology (AU J.T.), Assumption University, Thailand, Apr. 2009.
Vorapoj Patanavijit, Chaiyod Pirak and Gerd Ascheid, A Performance Impact of An Edge Kernel for The High-Frequency Image Prediction Reconstruction, ISCIT 2014, Incheon, Korea, Sep. 2014.
Vorapoj Patanavijit, Comparative Experimental Exploration of Robust Norm Functions for Iterative Super Resolution Reconstructions under Noise Surrounding, ECTI Transactions on EEC, ECTI Association, Thailand. Vol.13, No.2, August 2015.
Kornkamol Thakulsukanant and Vorapoj Patanavijit, A Novel Resolution Enhancement Established on An Iterative Regularized ML MSRR and High-Frequency Pre-Determining SSRR for Ultra-Magnification Rate, Proceeding of The 14th Annual International Conference of Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2017), ECTI Association Thailand, Phuket, Thailand, June 2017. (IEEE Xplore)
Zhouchen Lin and Heung-Yeung Shum, Fundamental Limits of Reconstruction-Based Superresolution Algorithms under Local Translation, IEEE Trans. PAMI., Vol. 26, No. Jan. 2004.