Up to now, an increase in camera resolution required image sensors with more and more pixels. However, acquisition systems are limited in their pixels per second throughput given as power and complexity constraints. Simply capturing more pixels in a given system is often not possible. We propose a new non-regular imaging architecture that samples only few pixels and reconstructs a high resolution image afterwards. Our sampling is optimized to provide non-regular spatial sampling from a sensor with regular readout circuits. An existing slow image acquisition system can then be used to capture the data. The image reconstruction is performed with a local sparsity-based approach. The result is a high resolution image that requires a much smaller effort during acquisition
Capturing large fields of view with only one camera is an important aspect in surveillance and automotive applications, but the wide-angle fisheye imagery thus obtained exhibits very special characteristics that may not be very well suited for typical image and video processing methods such as motion estimation. This paper introduces a motion estimation method that adapts to the typical radial characteristics of fisheye video sequences by making use of an equisolid reprojection after moving part of the motion vector search into the perspective domain via a corresponding back-projection. By combining this approach with conventional translational motion estimation and compensation, average gains in luminance PSNR of up to 1.14 dB are achieved for synthetic fisheye sequences and up to 0.96 dB for real-world data. Maximum gains for selected frame pairs amount to 2.40 dB and 1.39 dB for synthetic and real-world data, respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.