The response of indirect x-ray digital imaging sensors is often not homogenous on the entire surface area. In this case, calibration is needed to build offset and gain maps, which are used to correct the sensor output. The sensors of new generation are equipped with an on-board memory, which serves to store these maps. However, because of its limited dimension, the maps have to be compressed before saving them. This step is critical because of the extremely high compression rate required. The authors propose here a novel method to achieve such a high compression rate, without degrading the quality of the sensor output. It is based on quad tree decomposition, which performs an adaptive sampling of the offset and gain maps, matched with a RBF-based interpolation strategy. The method was tested on a typical intraoral radiographic sensor and compared with traditional compression techniques. Qualitative and quantitative results show that the method achieves a higher compression rate and produces images of superior quality. The method can be adopted also in different fields where a high compression rate is required.

Compression and smart coding of offset ad gain maps for intraoral digital x-ray sensors / I. Frosio, N.A. Borghese. - In: MEDICAL PHYSICS. - ISSN 0094-2405. - 36:2(2009 Feb), pp. 464-479.

Compression and smart coding of offset ad gain maps for intraoral digital x-ray sensors

I. Frosio
Primo
;
N.A. Borghese
Ultimo
2009

Abstract

The response of indirect x-ray digital imaging sensors is often not homogenous on the entire surface area. In this case, calibration is needed to build offset and gain maps, which are used to correct the sensor output. The sensors of new generation are equipped with an on-board memory, which serves to store these maps. However, because of its limited dimension, the maps have to be compressed before saving them. This step is critical because of the extremely high compression rate required. The authors propose here a novel method to achieve such a high compression rate, without degrading the quality of the sensor output. It is based on quad tree decomposition, which performs an adaptive sampling of the offset and gain maps, matched with a RBF-based interpolation strategy. The method was tested on a typical intraoral radiographic sensor and compared with traditional compression techniques. Qualitative and quantitative results show that the method achieves a higher compression rate and produces images of superior quality. The method can be adopted also in different fields where a high compression rate is required.
digital radiography; quad tree decomposition; sensor calibration; X-ray
Settore INF/01 - Informatica
Article (author)
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/62316
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 3
social impact