Camera Spatial Frequency Response Derived from Pictorial Natural Scenes

Van Zwanenberg, O. 2022. Camera Spatial Frequency Response Derived from Pictorial Natural Scenes. PhD thesis University of Westminster School of Computer Science and Engineering https://doi.org/10.34737/vvqxq

TitleCamera Spatial Frequency Response Derived from Pictorial Natural Scenes
TypePhD thesis
AuthorsVan Zwanenberg, O.
Abstract

Camera system performance is a prominent part of many aspects of imaging science and computer vision. There are many aspects to camera performance that determines how accurately the image represents the scene, including measurements of colour accuracy, tone reproduction, geometric distortions, and image noise evaluation. The research conducted in this thesis focuses on the Modulation Transfer Function (MTF), a widely used camera performance measurement employed to describe resolution and sharpness. Traditionally measured under controlled conditions with characterised test charts, the MTF is a measurement restricted to laboratory settings. The MTF is based on linear system theory, meaning the input to output must follow a straightforward correlation. Established methods for measuring the camera system MTF include the ISO12233:2017 for measuring the edge-based Spatial Frequency Response (e-SFR), a sister measure of the MTF designed for measuring discrete systems.
Many modern camera systems incorporate non-linear, highly adaptive image signal processing (ISP) to improve image quality. As a result, system performance becomes scene and processing dependant, adapting to the scene contents captured by the camera. Established test chart based MTF/SFR methods do not describe this adaptive nature; they only provide the response of the camera to a test chart signal. Further, with the increased use of Deep Neural Networks (DNN) for image recognition tasks and autonomous vision systems, there is an increased need for monitoring system performance outside laboratory conditions in real-time, i.e. live-MTF. Such measurements would assist in monitoring the camera systems to ensure they are fully operational for decision critical tasks.
This thesis presents research conducted to develop a novel automated methodology that estimates the standard e-SFR directly from pictorial natural scenes. This methodology has the potential to produce scene dependant and real-time camera system performance measurements, opening new possibilities in imaging science and allowing live monitoring/calibration of systems for autonomous computer vision applications.
The proposed methodology incorporates many well-established image processes, as well as others developed for specific purposes. It is presented in two parts.
Firstly, the Natural Scene derived SFR (NS-SFR) are obtained from isolated captured scene step-edges, after verifying that these edges have the correct profile for implementing into the slanted-edge algorithm. The resulting NS-SFRs are shown to be a function of both camera system performance and scene contents. The second part of the methodology uses a series of derived NS-SFRs to estimate the system e-SFR, as per the ISO12233 standard. This is achieved by applying a sequence of thresholds to segment the most likely data corresponding to the system performance. These thresholds a) group the expected optical performance variation across the imaging circle within radial distance segments, b) obtain the highest performance NS-SFRs per segment and c) select the NS-SFRs with input edge and region of interest (ROI) parameter ranges shown to introduce minimal e-SFR variation. The selected NS-SFRs are averaged per radial segment to estimate system e-SFRs across the field of view. A weighted average of these estimates provides an overall system performance estimation.
This methodology is implemented for e-SFR estimation of three characterised camera systems, two near-linear and one highly non-linear. Investigations are conducted using large, diverse image datasets as well as restricting scene content and the number of images used for the estimation. The resulting estimates are comparable to ISO12233 e-SFRs derived from test chart inputs for the near-linear systems. Overall estimate stays within one standard deviation of the equivalent test chart measurement. Results from the highly non-linear system indicate scene and processing dependency, potentially leading to a more representative SFR measure than the current chart-based approaches for such systems. These results suggest that the proposed method is a viable alternative to the ISO technique.

Year2022
File
File Access Level
Open (open metadata and files)
PublisherUniversity of Westminster
Publication dates
PublishedMar 2022
Digital Object Identifier (DOI)https://doi.org/10.34737/vvqxq

Related outputs

Analysis of Natural Scene Derived Spatial Frequency Responses for Estimating Camera ISO12233 Slanted-edge Performance
van Zwanenberg, Oliver, Triantaphillidou, Sophie, Psarrou, Alexandra and Jenkin, Robin B. 2021. Analysis of Natural Scene Derived Spatial Frequency Responses for Estimating Camera ISO12233 Slanted-edge Performance. Journal of Imaging Science and Technology. https://doi.org/10.2352/j.imagingsci.technol.2021.65.6.060405

Estimation of ISO12233 Edge Spatial Frequency Response from Natural Scene Derived Step-Edge Data
van Zwanenberg, Oliver, Triantaphillidou, Sophie, Jenkin, Robin B. and Psarrou, Alexandra 2021. Estimation of ISO12233 Edge Spatial Frequency Response from Natural Scene Derived Step-Edge Data. Journal of Imaging Science and Technology. 65 (6), pp. 60402-1-60402-16. https://doi.org/10.2352/j.imagingsci.technol.2021.65.6.060402

Natural Scene Derived Camera Edge Spatial Frequency Response for Autonomous Vision Systems
Van Zwanenberg, O., Triantaphillidou, S., Jenkin, R. and Psarrou, A. 2021. Natural Scene Derived Camera Edge Spatial Frequency Response for Autonomous Vision Systems. IS&T/IoP London Imaging Meeting 2021. London 20 - 22 Sep 2021 The Society of Imaging Science and Technology. https://doi.org/10.2352/issn.2694-118X.2021.LIM-88

Camera System Performance Derived from Natural Scenes
Van Zwanenberg, O., Triantaphillidou, S., Jenkin, R. and Psarrou, A. 2020. Camera System Performance Derived from Natural Scenes. Bonnier, Nicolas and Farias, Mylène (ed.) IS&T Electronic Imaging: Image Quality and System Performance XVII. Burlingame, California, USA 26 - 30 Jan 2020 The Society of Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2020.9.IQSP-241

Edge Detection Techniques for Quantifying Spatial Imaging System Performance and Image Quality
Van Zwanenberg, O., Triantaphillidou, S., Jenkin, R. and Psarrou, A. 2019. Edge Detection Techniques for Quantifying Spatial Imaging System Performance and Image Quality. The Conference on Computer Vision and Pattern Recognition (CVPR 2019). Long Beach California 15 - 21 Jun 2019 ACM/IEEE. https://doi.org/10.1109/CVPRW.2019.00238

Permalink - https://westminsterresearch.westminster.ac.uk/item/vvqxq/camera-spatial-frequency-response-derived-from-pictorial-natural-scenes


Share this

Usage statistics

53 total views
44 total downloads
These values cover views and downloads from WestminsterResearch and are for the period from September 2nd 2018, when this repository was created.