ArticleSensors (Basel, Switzerland)2008
Spectral-Based Blind Image Restoration Method for Thin TOMBO Imagers.
Article in Sensors (Basel, Switzerland), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A hybrid spatial blur detection and restoration algorithm for smartphone captured document images.Scientific reports · 2026Article
- Ensemble Dictionary Learning for Single Image Deblurring via Low-Rank Regularization.Sensors (Basel, Switzerland) · 2019Article
- Defocus Blur Detection and Estimation from Imaging Sensors.Sensors (Basel, Switzerland) · 2018Article
- Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.Sensors (Basel, Switzerland) · 2017Article
- Fast image restoration for spatially varying defocus blur of imaging sensor.Sensors (Basel, Switzerland) · 2015Article
- A High Resolution Color Image Restoration Algorithm for Thin TOMBO Imaging Systems.Sensors (Basel, Switzerland) · 2009Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the recent advances in microelectronic fabrication technology, it becomes now possible to fabricate thin imagers, less than half a millimeter thick. Dubbed TOMBO (an acronym for thin observation module by bound optics), a thin camera-on-a-chip integrates micro-optics and photo-sensing elements, together with advanced processing circuitry, all on a single silicon chip. Modeled after the compound-eye found in insects and many other arthropods, the TOMBO imager captures simultaneously a mosaic of low resolution images. In this paper, we describe and analyze a novel spectral-based blind algorithm that enables the restoration of a high resolution image from the captured low resolution images.The proposed blind restoration method does not require prior information about the imaging system nor the original scene. Furthermore, it alleviates the need for conventional de-shading and rearrangement processing techniques. Experimental results demonstrate that the proposed method can restore images for SNER lower than 3dB.
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Registered trials
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