Analysis of Natural Scene Derived Spatial Frequency Responses for Estimating Camera ISO12233 Slanted-edge Performance

The Natural Scene derived Spatial Frequency Response (NS-SFR) framework automatically extracts suitable step-edges from natural pictorial scenes and processes these edges via the edge-based ISO12233 (e-SFR) algorithm. Previously, a novel methodology was presented to estimate the standard e-SFR from NS-SFR data. This paper implements this method using diverse natural scene image datasets from three characterized camera systems. Quantitative analysis was carried out on the system e-SFR estimates to validate accuracy of the method. Both linear and non-linear camera systems were evaluated. To investigate how scene content and dataset size affect system e-SFR estimates, analysis was conducted on entire datasets, as well as subsets of various sizes and scene group types. Results demonstrate that system e-SFR estimates strongly correlate with results from test chart inputs, with accuracy comparable to that of the ISO12233. Further work toward improving and fine-tuning the proposed methodology for practical implementation is discussed.

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Estimation of ISO12233 Edge Spatial Frequency Response from Natural Scene Derived Step-Edge Data

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2021.65.6.060402 ◽

2021 ◽

Author(s):

Oliver van Zwanenberg ◽

Sophie Triantaphillidou ◽

Robin B. Jenkin ◽

Alexandra Psarrou

Keyword(s):

Spatial Frequency ◽

Frequency Response ◽

System Performance ◽

Performance Measure ◽

Natural Scenes ◽

Natural Scene ◽

Performance Measurements ◽

Camera System ◽

Edge Based ◽

System Performance Measure

The Natural Scene derived Spatial Frequency Response (NS-SFR) is a novel camera system performance measure that derives SFRs directly from images of natural scenes and processes them using ISO12233 edge-based SFR (e-SFR) algorithm. NS-SFR is a function of both camera system performance and scene content. It is measured directly from captured scenes, thus eliminating the use of test charts and strict laboratory conditions. The effective system e-SFR can be subsequently estimated from NS-SFRs using statistical analysis and a diverse dataset of scenes. This paper first presents the NS-SFR measuring framework, which locates, isolates, and verifies suitable step-edges from captures of natural scenes. It then details a process for identifying the most likely NS-SFRs for deriving the camera system e-SFR. The resulting estimates are comparable to standard e-SFRs derived from test chart inputs, making the proposed method a viable alternative to the ISO technique, with potential for real-time camera system performance measurements.

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Natural Scene Derived Camera Edge Spatial Frequency Response for Autonomous Vision Systems

London Imaging Meeting ◽

10.2352/issn.2694-118x.2021.lim-88 ◽

2021 ◽

Vol 2021 (1) ◽

pp. 88-92

Author(s):

Oliver van Zwanenberg ◽

Sophie Triantaphillidou ◽

Robin B. Jenkin ◽

Alexandra Psarrou

Keyword(s):

Linear System ◽

Spatial Frequency ◽

Frequency Response ◽

Real Time ◽

Natural Scene ◽

Vision Systems ◽

Camera System ◽

Non Linear ◽

Edge Based ◽

Non Linear System

The edge-based Spatial Frequency Response (e-SFR) is an established measure for camera system quality performance, traditionally measured under laboratory conditions. With the increasing use of Deep Neural Networks (DNNs) in autonomous vision systems, the input signal quality becomes crucial for optimal operation. This paper proposes a method to estimate the system e-SFR from pictorial natural scene derived SFRs (NSSFRs) as previously presented, laying the foundation for adapting the traditional method to a real-time measure.In this study, the NS-SFR input parameter variations are first investigated to establish suitable ranges that give a stable estimate. Using the NS-SFR framework with the established parameter ranges, the system e-SFR, as per ISO 12233, is estimated. Initial validation of results is obtained from implementing the measuring framework with images from a linear and a non-linear camera system. For the linear system, results closely approximate the ISO 12233 e-SFR measurement. Non-linear system measurements exhibit scene-dependant characteristics expected from edge-based methods. The requirements to implement this method in real-time for autonomous systems are then discussed.

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Photography. Electronic still picture imaging. Resolution and spatial frequency responses

10.3403/30254317 ◽

2014 ◽

Keyword(s):

Spatial Frequency ◽

Frequency Responses ◽

Imaging Resolution

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Modulated imaging: quantitative analysis and tomography of turbid media in the spatial-frequency domain

Optics Letters ◽

10.1364/ol.30.001354 ◽

2005 ◽

Vol 30 (11) ◽

pp. 1354 ◽

Cited By ~ 256

Author(s):

David J. Cuccia ◽

Frederic Bevilacqua ◽

Anthony J. Durkin ◽

Bruce J. Tromberg

Keyword(s):

Quantitative Analysis ◽

Spatial Frequency ◽

Frequency Domain ◽

Turbid Media ◽

Modulated Imaging ◽

Spatial Frequency Domain

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The Computation of Binocular Edges

Perception ◽

10.1068/p090069 ◽

1980 ◽

Vol 9 (1) ◽

pp. 69-86 ◽

Cited By ~ 48

Author(s):

John E W Mayhew ◽

John P Frisby

Keyword(s):

Spatial Frequency ◽

Computational Model ◽

Stereo Pair ◽

Natural Scene ◽

Edge Information ◽

Distinctive Features ◽

Zero Crossings ◽

Random Dot Stereogram

A computational model is described which effects the binocular combination of monocular edge information. The distinctive features of the model are: (i) it identifies edge locations in each monocular field by searching for zero crossings in nonorientated centre-surround convolution profiles; (ii) it selects amongst all possible binocular point-for-point combinations of edge locations only those which satisfy a (quasi-)collinear figural grouping rule; (iii) it presents a concept of the orientated and spatial-frequency-tuned channel as a nonlinear grouping operator. The success of the model is demonstrated both on a stereo pair of a natural scene and on a random-dot stereogram.

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Generalized Spiral Spring: A Bioinspired Tunable Stiffness Mechanism for Linear Response With High Resolution

Journal of Mechanisms and Robotics ◽

10.1115/1.4045654 ◽

2020 ◽

Vol 13 (1) ◽

Cited By ~ 1

Author(s):

Zeeshan Qaiser ◽

Shane Johnson

Keyword(s):

Analytical Model ◽

Compliant Mechanisms ◽

Virtual Work ◽

Beam Theory ◽

Industrial Robots ◽

Fine Tuning ◽

Practical Implementation ◽

Positioning Systems ◽

Spiral Spring ◽

Multiobjective Design

Abstract Compliant mechanisms are typically designed for varying stiffness from nearly zero to rigid. However, targeted design for fine-tuning within an application's sensitive range of stiffness remains more desirable for practical implementation in accurate loading or positioning systems. To achieve various competing objectives, a “generalized spiral spring” (GSS) is proposed which achieves small size and other objectives by using a reduced number of parameters as provided by the spiral shape description of the components. An analytical model based on virtual work and curved beam theory is developed for accurate prediction of the stiffness. Moreover, finite element (FE) models are also developed for verification of the proposed designs. Multiobjective design optimization (MDO) is conducted to maximize the linearity in the stiffness versus control parameter (CP) response and improve resolution. The proposed analytical model is validated experimentally and computationally. This approach may be used to achieve finesse by accurate positioning with force control for industrial robots and elegant prostheses.

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The role of edge-based and surface-based information in natural scene categorization: Evidence from behavior and event-related potentials

Consciousness and Cognition ◽

10.1016/j.concog.2016.06.008 ◽

2016 ◽

Vol 43 ◽

pp. 152-166 ◽

Cited By ~ 5

Author(s):

Qiufang Fu ◽

Yong-Jin Liu ◽

Zoltan Dienes ◽

Jianhui Wu ◽

Wenfeng Chen ◽

...

Keyword(s):

Event Related Potentials ◽

Natural Scene ◽

Scene Categorization ◽

Related Potentials ◽

Edge Based

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Residual abilities in age-related macular degeneration to process spatial frequencies during natural scene categorization

Visual Neuroscience ◽

10.1017/s0952523811000435 ◽

2011 ◽

Vol 28 (6) ◽

pp. 529-541 ◽

Cited By ~ 9

Author(s):

BENOIT MUSEL ◽

RUXANDRA HERA ◽

SYLVIE CHOKRON ◽

DAVID ALLEYSSON ◽

CHRISTOPHE CHIQUET ◽

...

Keyword(s):

Spatial Frequency ◽

Macular Degeneration ◽

Reaction Times ◽

Age Related Macular Degeneration ◽

Natural Scenes ◽

Natural Scene ◽

Scene Categorization ◽

Age Related ◽

Spatial Frequencies ◽

Healthy Participants

AbstractAge-related macular degeneration (AMD) is characterized by a central vision loss. We explored the relationship between the retinal lesions in AMD patients and the processing of spatial frequencies in natural scene categorization. Since the lesion on the retina is central, we expected preservation of low spatial frequency (LSF) processing and the impairment of high spatial frequency (HSF) processing. We conducted two experiments that differed in the set of scene stimuli used and their exposure duration. Twelve AMD patients and 12 healthy age-matched participants in Experiment 1 and 10 different AMD patients and 10 healthy age-matched participants in Experiment 2 performed categorization tasks of natural scenes (Indoors vs. Outdoors) filtered in LSF and HSF. Experiment 1 revealed that AMD patients made more no-responses to categorize HSF than LSF scenes, irrespective of the scene category. In addition, AMD patients had longer reaction times to categorize HSF than LSF scenes only for indoors. Healthy participants’ performance was not differentially affected by spatial frequency content of the scenes. In Experiment 2, AMD patients demonstrated the same pattern of errors as in Experiment 1. Furthermore, AMD patients had longer reaction times to categorize HSF than LSF scenes, irrespective of the scene category. Again, spatial frequency processing was equivalent for healthy participants. The present findings point to a specific deficit in the processing of HSF information contained in photographs of natural scenes in AMD patients. The processing of LSF information is relatively preserved. Moreover, the fact that the deficit is more important when categorizing HSF indoors, may lead to new perspectives for rehabilitation procedures in AMD.

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Using the dead leaves pattern for more than spatial frequency response measurements

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.16.avm-110 ◽

2020 ◽

Vol 2020 (16) ◽

pp. 148-1-148-6

Author(s):

Uwe Artmann

Keyword(s):

Image Quality ◽

Light Intensity ◽

Spatial Frequency ◽

Noise Reduction ◽

Frequency Response ◽

Dynamic Range ◽

Video Streams ◽

Camera System ◽

Camera Systems ◽

The Dead

The dead leaves pattern is very useful to obtain an SFR from a stochastic pattern and can be used to measure texture loss due to noise reduction or compression in images and video streams. In this paper, we present results from experiments that use the pattern and different analysis approaches to measure the dynamic range of a camera system as well as to describe the dependency of the SFR on object contrast and light intensity. The results can be used to improve the understanding of the performance of modern camera systems. These systems work adaptively and are scene aware but are not well described by standard image quality metrics.

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