An edge-guided image interpolation algorithm via directional filtering and data fusion
- PMID: 16900678
- DOI: 10.1109/tip.2006.877407
An edge-guided image interpolation algorithm via directional filtering and data fusion
Abstract
Preserving edge structures is a challenge to image interpolation algorithms that reconstruct a high-resolution image from a low-resolution counterpart. We propose a new edge-guided nonlinear interpolation technique through directional filtering and data fusion. For a pixel to be interpolated, two observation sets are defined in two orthogonal directions, and each set produces an estimate of the pixel value. These directional estimates, modeled as different noisy measurements of the missing pixel are fused by the linear minimum mean square-error estimation (LMMSE) technique into a more robust estimate, using the statistics of the two observation sets. We also present a simplified version of the LMMSE-based interpolation algorithm to reduce computational cost without sacrificing much the interpolation performance. Experiments show that the new interpolation techniques can preserve edge sharpness and reduce ringing artifacts.
Similar articles
-
Contrast-guided image interpolation.IEEE Trans Image Process. 2013 Nov;22(11):4271-85. doi: 10.1109/TIP.2013.2271849. Epub 2013 Jul 3. IEEE Trans Image Process. 2013. PMID: 23846469
-
Color demosaicking via directional linear minimum mean square-error estimation.IEEE Trans Image Process. 2005 Dec;14(12):2167-78. doi: 10.1109/tip.2005.857260. IEEE Trans Image Process. 2005. PMID: 16370469
-
Superresolution and noise filtering using moving least squares.IEEE Trans Image Process. 2006 Aug;15(8):2239-48. doi: 10.1109/tip.2006.877406. IEEE Trans Image Process. 2006. PMID: 16900679
-
Edge-based image restoration.IEEE Trans Image Process. 2005 Oct;14(10):1454-68. doi: 10.1109/tip.2005.854466. IEEE Trans Image Process. 2005. PMID: 16238052
-
Nonlinear fisher discriminant analysis using a minimum squared error cost function and the orthogonal least squares algorithm.Neural Netw. 2002 Mar;15(2):263-70. doi: 10.1016/s0893-6080(01)00142-3. Neural Netw. 2002. PMID: 12022513 Review.
Cited by
-
Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.Sensors (Basel). 2015 May 22;15(5):12053-79. doi: 10.3390/s150512053. Sensors (Basel). 2015. PMID: 26007744 Free PMC article.
-
Blind-label subwavelength ultrasound imaging.Sci Adv. 2025 Jan 31;11(5):eado2826. doi: 10.1126/sciadv.ado2826. Epub 2025 Jan 29. Sci Adv. 2025. PMID: 39879291 Free PMC article.
-
Edge-Enhanced with Feedback Attention Network for Image Super-Resolution.Sensors (Basel). 2021 Mar 15;21(6):2064. doi: 10.3390/s21062064. Sensors (Basel). 2021. PMID: 33804241 Free PMC article.
-
Efficient Image Super-Resolution via Self-Calibrated Feature Fuse.Sensors (Basel). 2022 Jan 2;22(1):329. doi: 10.3390/s22010329. Sensors (Basel). 2022. PMID: 35009871 Free PMC article.
-
Optimal Diagnostic Indices for Idiopathic Normal Pressure Hydrocephalus Based on the 3D Quantitative Volumetric Analysis for the Cerebral Ventricle and Subarachnoid Space.AJNR Am J Neuroradiol. 2015 Dec;36(12):2262-9. doi: 10.3174/ajnr.A4440. Epub 2015 Sep 10. AJNR Am J Neuroradiol. 2015. PMID: 26359148 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
