Paper Info
Title
Increasing Imaging Resolution by Non-Regular Sampling and Joint Sparse Deconvolution and Extrapolation.
Abstract
Increasing the resolution of image sensors has been a never ending struggle since many years. In this paper, we propose a novel image sensor layout, which allows for the acquisition of images at a higher resolution and improved quality. For this, the image sensor makes use of non-regular sampling, which reduces the impact of aliasing. Therewith, it allows for capturing details, which would not be possible with state-of-the-art sensors of the same number of pixels. The non-regular sampling is achieved by rotating prototype pixel cells in a non-regular fashion. As not the whole area of the pixel cell is sensitive to light, a non-regular spatial integration of the incident light is obtained. Based on the sensor output data, a high-resolution image can be reconstructed by performing a deconvolution with respect to the integration area and an extrapolation of the information to the insensitive regions of the pixels. To solve this challenging task, we introduce a novel joint sparse deconvolution and extrapolation algorithm. The union of non-regular sampling and the proposed reconstruction allows for achieving a higher resolution and therewith an improved imaging quality.
Year
DOI
Venue
2019
10.1109/TCSVT.2018.2796725
IEEE Trans. Circuits Syst. Video Techn.
Keywords
Field
DocType
Image sensors,Sensors,Image resolution,Image reconstruction,Layout,Reconstruction algorithms,Prototypes
Iterative reconstruction,Computer vision,Image sensor,Computer science,Deconvolution,Aliasing,Extrapolation,Pixel,Sampling (statistics),Artificial intelligence,Image resolution
Journal
Volume
Issue
ISSN
29
2
1051-8215
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Jürgen Seiler114528.28
Markus Jonscher2154.38
Thomas Ussmueller344.54
André Kaup4861127.24