Title
The gigavision camera
Abstract
We propose a new image device called gigavision camera. The main differences between a conventional and a gigavision camera are that the pixels of the gigavision camera are binary and orders of magnitude smaller. A gigavision camera can be built using standard memory chip technology, where each memory bit is designed to be light sensitive. A conventional gray level image can be obtained from the binary gigavision image by low-pass filtering and sampling. The main advantage of the gigavision camera is that its response is non-linear and similar to a logarithmic function, which makes it suitable for acquiring high dynamic range scenes. The larger the number of binary pixels considered, the higher the dynamic range of the gigavision camera will be. In addition, the binary sensor of the gigavision camera can be combined with a lens array in order to realize an extremely thin camera. Due to the small size of the pixels, this design does not require deconvolution techniques typical of similar systems based on conventional sensors.
Year
DOI
Venue
2009
10.1109/ICASSP.2009.4959778
ICASSP
Keywords
Field
DocType
binary sensor,dynamic range,conventional gray level image,logarithmic sensor response,new image device,conventional sensor,high dynamic range scene,thin camera,gigavision camera,index terms— high dynamic range imaging,binary pixel,computational photography,binary gigavision image,indexing terms,layout,low pass filters,filtering,image sensors,logarithmic function,deconvolution,low pass filter,pixel,noise,chip,lenses,photonics,image resolution
Computer vision,Dynamic range,Computer graphics (images),Image sensor,Computer science,Computational photography,Deconvolution,Pixel,Artificial intelligence,High dynamic range,Image resolution,High-dynamic-range imaging
Conference
ISSN
Citations 
PageRank 
1520-6149
2
0.57
References 
Authors
4
5
Name
Order
Citations
PageRank
Luciano Sbaiz18411.42
Feng Yang28611.70
Edoardo Charbon338574.69
Sabine Süsstrunk44984207.02
Martin Vetterli5139262397.68