# Experimental and simulation results for inherent film unsharpness considering screens and cassette contributions

Anthony Touron, Kassem Kalo, Romain Jonchiere, Andreas Schumm, Uwe Zscherpel

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## To cite this version:

Anthony Touron, Kassem Kalo, Romain Jonchiere, Andreas Schumm, Uwe Zscherpel. Experimental and simulation results for inherent film unsharpness considering screens and cassette contributions. e-Journal of Nondestructive Testing, 2025, Special Issue of e-Journal of Nondestructive Testing (eJNDT), 30 (8), 10.5828/31400.cea-05516028

HAL Id: cea-05516028

https://cea.hal.science/cea-05516028v1

Submitted on 17 Feb 2026

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
# Experimental and simulation results for inherent film unsharpness considering screens and cassette contributions

Anthony TOURON¹*, Kassem KALO², Romain JONCHIERE², Andreas SCHUMM³, Uwe ZSCHERPEL⁴

¹Université Paris-Saclay, CEA List, Palaiseau, France

²EDF, Direction of Industrial Quality, Saint Denis, France

³EDF Lab les Renardières, Moret sur Loing, France

⁴BAM, Berlin, Germany

## Abstract

In industrial radiography, total unsharpness is typically defined as the square root of the sum of squared geometrical and inherent unsharpness, with motion unsharpness often negligible. While geometrical unsharpness can be controlled by adjusting source-object-detector distances, inherent detector unsharpness depends on radiation energy and is caused by secondary radiation within screens and cassette, affecting nearby silver halide grains of the film.

While it is relatively straightforward to determine inherent unsharpness for digital radiography, it is not the case for film radiography. However, a detailed comparison of this unsharpness between these two techniques is important for transitioning from one to the other, with implications for industrial implementation or regulatory requirements.

This study presents the results obtained through simulation and experiments on measuring this unsharpness in film radiography using different methods, including Klasens method [1], which involves evaluation of the profile of a particular edge image. Experiments were conducted using various films, cassette types, screens, and gamma sources ($^{75}$Se, $^{192}$Ir, $^{60}$Co) to study the influence of these various parameters on unsharpness. Results confirm that inherent unsharpness, with increasing energy, is significant and must be considered.

**Keywords:** X-ray radiography with gamma sources, Argentic film, Klasens Method, Inherent unsharpness, X-ray simulation

## 1. Introduction

Radiographic testing (RT) is a widely used nondestructive testing technique that enables the detection and characterization of internal flaws in materials through the analysis of radiographic images. The effectiveness of flaw detection in radiographic images is primarily governed by three factors: contrast, granularity and unsharpness [2]. While contrast and granularity can be optimized through appropriate selection of film system class and exposure parameters, unsharpness remains a critical limiting factor in image quality and flaw detectability.

Total unsharpness in radiography encompasses both source geometric unsharpness and inherent detector unsharpness. The geometric component, arising from the spatial configuration of the source, object, and detector, is well understood and generally controlled by radiographers during inspection planning. Inherent unsharpness, however, is more complex

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and challenging to reduce. It stems from physical phenomena occurring within the radiographic cassette, particularly photon scattering (Compton and Rayleigh interactions) in the metal amplification screens which are in contact with the film emulsions and the spatial broadening of secondary radiation that activates silver halide grains across a distributed area. These effects blur the recorded image and degrade spatial resolution, making a precise evaluation of inherent unsharpness crucial for reliable defect detection.

To assess and quantify inherent unsharpness, several standardized methods are available. The use of Image Quality Indicators (IQIs), such as the Duplex Plate IQI (ASTM E3388) and Duplex Wire IQI (NF EN ISO 19232-5 and ASTM E2002), provides a practical means to determine the smallest resolvable feature, thereby estimating spatial resolution. Additional techniques include Klasens' method [1], which calculates unsharpness from the slope of an edge profile, generated by a swiveling copper edge (NF EN IEC 62976) or a tungsten edge (IEC 62220-1).

This study aims to characterize inherent unsharpness in film radiography through a combined simulation and experimental approach for various configurations and high energy gamma sources ($^{75}$Se, $^{192}$Ir, $^{60}$Co).

## 2. Material and Methods

The CIVA software [3] enables full simulation of radiographic inspections by modeling the entire imaging process, from photon emission to optical density rendering. Photons emitted by an X-ray tube or a radionuclide are propagated through the radiographic scene using ray tracing techniques that incorporate scatter phenomena such as Compton scattering, Rayleigh scattering, and pair production. The simulation adheres to the NF EN ISO 11699 standard, converting air kerma values to optical densities of the exposed screen/film combination. A comprehensive model simulates the interaction of photons with the radiographic cassette, including the generation of electrons within the screens and film emulsions, leading to seeds of silver halide grains. They are converted to dark metallic silver during the film development process. Only elastic interactions are considered for the electron tracking as shown in Figure 1, and we consider the Continuous Slowing Down Approximation (CSDA) to compute the energy lost by the electron between two interactions. The Nutting model [4], [5] is then employed to relate the number of exposed grains within each 50 µm pixel to the resulting optical density, with key parameters fixed: a film emulsion thickness of 42 µm (both emulsions), a log-normal distribution for the grain radius with a mean of 0.360 µm and a standard deviation of 0.22 µm, and a grain density of $1.071 \times 10^9$ per mm³. Due to the detailed physical modeling, simulations require significant computation time and are parallelized using Intel Threading Building Blocks, but they are still taking several days to complete.
<figure><img src="image_4.png" /><figcaption>Figure 1 - Simulation setup + Illustration of the electron transport model with exposure of silver halide grains.</figcaption></figure>

### 3. Experimental Setup

Experimental validations were carried out at CAP AIN (Selenium-75 & Iridium-192) and BAM (Cobalt-60) using a vertical cassette setup to minimize scatter contributions, as shown in Figure 2. Radiographic exposures were performed with various radionuclide sources, including Selenium-75 (3 mm thickness × 3 mm diameter, 55.38 Ci), Iridium-192 (2.7 mm thickness × 3.375 mm diameter, 41.5 Ci), and Cobalt-60 (3 mm thickness × 4 mm diameter, 27.2 Ci), all positioned at a fixed source-to-film distance of 1.5 meters. The radiographic films measured 10 × 24 cm² and were enclosed in Vacupac envelopes with 27 µm lead screens; in some tests, additional lead screens of 100 to 250 µm were included, though these were not considered in the current analysis. Two film system classes, C2 and C5, according to ISO 11699-1 were utilized, and object thickness was simulated using a steel plate of 20 mm. Image quality and unsharpness were assessed using various specimen from different standards: a Duplex Plate Image Quality Indicator (IQI) following ASTM E3388, a Duplex Wire IQI following NF EN ISO 19232-5, a swiveling copper edge (16 mm thick) in accordance with NF EN IEC 62976, and a polished edge on a 1 mm thick tungsten plate according to the medical DQE standard IEC 62220-1. Additional hole-type IQI (ASTM E1025) was prepared too, but needed further analysis, which is not done in this study.

<figure><img src="image_5.png" /><figcaption>Figure 2 - Picture of the experiment carried out at CAP AIN with the cassette positioned vertically to reduce the scatter. We can observe from left to right: Tungsten edge, Copper edge, Duplex wire IQI, Duplex plate IQI and Hole IQI.</figcaption></figure>
## 4. Results

Simulated radiographs focusing on key features – namely the tungsten edge, copper edge, and Duplex IQIs – are presented in Figure 3, with unsharpness results summarized in Table 1 for both experimental and simulated configurations. Experimental edge evaluations and their problems are presented Figure 5. For digitization of the films, the set-up “BAM-FDS3” was used, incorporating a LED light box with 8 kcd/m², a 15 MPix Basler CMOS camera, a variable exposure time control below 20 ms/frame and averaging of 100 frames for highest contrast sensitivity.

Quantitative analysis of unsharpness for the plate and edge was performed using Klasens' method, which evaluates the extrapolated distance between 14% and 86% gray level thresholds along the intensity profile across the edge image; examples of this evaluation is illustrated in Figure 4. For the Duplex IQI, the largest wire and plate pair resolved with less than 20% dip was used to determine the unsharpness value. An illustration of this evaluation on the Duplex IQI wire with interpolated basic spatial resolution, as specified in the NF EN ISO-19232-5 standard is shown Figure 6.

While literature values from references [2] and [6] were considered for comparison, the lack of detailed information regarding the original experimental setups – particularly for older sources like Halmshaw [2] – limits the accuracy of direct benchmarking.

<figure><img src="image_6.png" /><figcaption>Figure 3 - Simulated radiographs for ⁷⁵Se source without steel plate with zoom on the different specimens. Left to right: Tungsten edge, Copper edge, Duplex wire IQI (13 wire pairs) and Duplex plate IQI (10 plate pairs).</figcaption></figure>

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<figure><img src="image_8.png" /><figcaption>Figure 4 - Unsharpness measurement for ⁷⁵Se source without steel plate. Left: Result obtained with a Python script give an unsharpness of 0.13 mm. Right: Result obtained with Isee software also give an unsharpness of 0.13 mm.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Figure 5 – Unsharpness evaluation for ⁷⁵Se. Top: the evaluation of Klasens unsharpness (0,4 mm) is strongly disturbed by long range unsharpness contributions; Down: the evaluation of the 1st derivative of the edge profile (i.e., the line spread function) is not disturbed, the FWHM as indicated has to be multiplied by 1.3 for a Gaussian distribution to obtain the Klasens edge unsharpness value<fnref n="1" /> (0,1 mm).</figcaption></figure>

<footnote n="1">¹ There is a correction factor necessary to convert the FWHM value of the line spread function (i.e., the first derivative of the edge spread function) to the Klasens edge unsharpness value, which depends on the shape of the line spread function. This factor is 1.24 for Gaussian shape and 2.67 for Lorentzian shape, because the Lorentzian shape has wider tails that the Gaussian shape.</footnote>
<figure><img src="image_10.png" /><figcaption>Figure 6 – Interpolated basic spatial resolution (iSR<sub>b</sub>) obtained with Duplex Wire IQI with Dtect-x 2025.2 software. The interpolated total unsharpness being two times the basic spatial resolution. Left: <sup>75</sup>Se configuration with 20 mm steel plate with its profile lines. Right: <sup>192</sup>Ir configuration with 20 mm steel plate.</figcaption></figure>

<table><caption>Table 1 – Intrinsic film unsharpness (U<sub>f</sub>) results comparison between experience, simulation and literature.</caption><thead><tr><th></th><th>Exp. U<sub>f</sub> (mm)</th><th>Sim. U<sub>f</sub> (mm)</th><th>Lit. U<sub>f</sub> (mm)</th></tr></thead><tbody><tr><td><sup>75</sup>Se – no steel plate</td><td>0.10-0.13</td><td>0.12-0.14</td><td>0.18</td></tr><tr><td><sup>75</sup>Se – 20 mm steel plate</td><td>0.16-0.20</td><td>0.16-0.20</td><td>0.18</td></tr><tr><td><sup>192</sup>Ir – no steel plate</td><td>0.15-0.17</td><td>0.12-0.16</td><td>0.17-0.25</td></tr><tr><td><sup>192</sup>Ir – 20 mm steel plate</td><td>0.19-0.28</td><td>0.17</td><td>0.17-0.25</td></tr><tr><td><sup>60</sup>Co – no steel plate</td><td>No results</td><td>0.22-0.25</td><td>0.35</td></tr><tr><td><sup>60</sup>Co – 20 mm steel plate</td><td>0.26-0.32</td><td>No results</td><td>0.35</td></tr></tbody></table>

The comparison between experimental, simulated and literature intrinsic film unsharpness values is presented Table 1. The results are quite interesting in several aspects:

The unsharpness values are clearly dependent on source energy with values in this order: <sup>75</sup>Se < <sup>192</sup>Ir < <sup>60</sup>Co. Furthermore, additional steel plates increase the unsharpness as expected (by 0.02-0.07 mm for <sup>75</sup>Se and by 0.04-0.09 mm for <sup>192</sup>Ir).

We observe a good agreement between experimental and simulated unsharpness. Furthermore, even if they are limited due to the few information on their acquisition, the literature values seem to give a reasonably good approximation of inherent film unsharpness. Clearly it demonstrates the capability of simulation to predict complex physical parameters like unsharpness. To the best of our knowledge, this is the first time that a full physics model including secondary radiation has been used for industrial radiography simulation. The standard practice in simulation codes is to introduce inherent unsharpness in the form of image post processing to add additional blur, assuming the unsharpness of the source-film
system is known. Our model predicts the actual inherent unsharpness by simulating the physics involved, and is thus able to take the effect of screens and filters into account.

Finally, it shows that the inherent film unsharpness is far from negligible, especially for high energy source like $^{60}$Co, and it should be taken into account when silver and digital techniques are compared.

## 5. Discussion

The comparison between experimental and simulated radiographs revealed several critical considerations. Not all simulations achieved the expected optical density range of 2 to 3, leading to increased noise and a slight bias in unsharpness measurements, though this effect was mitigated by averaging over broader profile regions. Variability was observed between different specimen types (edges and IQIs), with unsharpness values consistently lower for the plate edge compared to the swiveling edge. To reduce aliasing artifacts, a slight angular rotation (2–5 degrees) of the Duplex plate and wire IQIs is recommended and should have been added in simulation. Additionally, the presence of a steel compensation plate, particularly when in contact with the detector, was noted to influence image quality by increasing unsharpness and reducing simulation speed.

We need to note that unsharpness measurements according to Klasens' method revealed some problems, which are caused by long-range scatter contributions. Indeed, the results depend a lot on the profile length and its width (we take the mean profile). Nevertheless, the use of the 1st derivative of the edge profile allowed us to evaluate unsharpness despite the long-range scatter.

Model limitations were also identified: the electron transport model includes only elastic collisions and does not take into account the variability of possible electron interactions, in particular inelastic and Bremsstrahlung. The fixed film thickness and grain distribution parameters in the film restrict simulation to a single film sensitivity. This information is difficult to obtain as it is not usually published by film manufacturers. Future enhancements include modeling different grain shapes and distributions to represent diverse film sensitivities, and accounting for potential fluorescence within the cassette, which will certainly further affect image sharpness.

On the numerical side, long computation times suggest a need for optimization through improved sampling algorithms and distributed computing using MPI protocols.

## 6. Conclusions

The literature data for inherent unsharpness is sparse, somewhat outdated, and do not always specify the full cassette/screen system for which it applies. At the same time, we know that inherent detector unsharpness is everything but neglectable for high energy gamma sources typically used in nuclear applications. With the transition to digital radiography, it is however
important to fully understand the inherent detector unsharpness we dealt with while using film radiography, to be able to specify reasonable target unsharpness for digital applications.

In this paper we have presented an evaluation of inherent unsharpness values using experiments and numerical simulation. Our study taught us a number of precautions to be taken when doing these experiments, and also highlighted the need for an accurate electron scattering model.

We intend to continue the simulation study with different cassette/screen systems, in particular with a thicker lead screen for ¹⁹²Ir and a steel screen for the ⁶⁰Co exposures, which are both more common in practice, and for which we already have experimental radiographic images, ready to be evaluated.

## Acknowledgements

The authors would like to express their sincere gratitude to Revollat T., Rouffiandis Y. and Thiely F. from CAP AIN for their invaluable support in carrying out the experimental work presented in this study.

## References

[1] H. A. Klasens, "Measurement and calculation of unsharpness combination in X-ray photography," *Phillips Res Rep.*, Vol.1 No. 4, August 1946.

[2] R. Halmshaw, *Industrial Radiology: Theory and practice*, vol. 1. in Non-Destructive Evaluation Series, vol. 1. Dordrecht: Springer Netherlands, 1995. doi: 10.1007/978-94-011-0551-4.

[3] R. Fernandez et al., "RT Modelling for NDT Recent and Future Developments in the CIVA RT/CT Module".

[4] P. G. Nutting, "On the absorption of light in heterogeneous media," *J. Wash. Acad. Sci.*, vol. 3, no. 11, pp. 322-326, 1913.

[5] E. A. de S. Goncalves, M. H. dos Santos, M. J. Anjos, L. F. de Oliveira, and R. de J. Associacao Brasileira de Energia Nuclear (ABEN), "Computational simulation of radiographic film," Associacao Brasileira de Energia Nuclear (ABEN), Rio de Janeiro, RJ (Brazil), INIS-BR--14721, Jan. 2013. Accessed: Apr. 14, 2025. [Online]. Available: https://inis.iaea.org/records/4cxrq-jtm83

[6] "industrial_radiography_image_forming_techniques.pdf." Accessed: Apr. 14, 2025. [Online]. Available: https://www.jwjndt.com/wp-content/uploads/2016/01/industrial_radiography_image_forming_techniques.pdf