Signal to Noise Ratio and Visual Noise of Mobile Phone Cameras

Peltoketo, Veli-Tapani

doi:10.2352/j.imagingsci.technol.2015.59.1.010401

Cited by 4 publications

(4 citation statements)

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“…The calculation of Dynamic Range (DR) according to ISO 15739:2013, revised in 2017 and 2023 [18], provides an estimation based on a patch with a density of 2.0, commonly found on semi-gloss reflective test charts (see Table I) [19]. This approach relies on chart values, like the tests presented in this work.…”

Section: B Dr Definition and Measurementmentioning

confidence: 99%

Camera Dynamic Range Measurement: The Role of Lenses and Target Spatial Distribution

Plutino,

Bagnati,

Rizzi

2024

IEEE Trans. Instrum. Meas.

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Section: B Dr Definition and Measurementmentioning

confidence: 99%

Camera Dynamic Range Measurement: The Role of Lenses and Target Spatial Distribution

Plutino,

Bagnati,

Rizzi

2024

IEEE Trans. Instrum. Meas.

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“…Noise arises from the effects of basic physics-the photon nature of light and the thermal energy of heat-inside image sensors and amplifiers. The total noise value is a complex mixture of several noise sources of lens system, pixel size, sensor technology and manufacturing, image processing pipeline, ISO speed, exposure time, RAW conversion [25]. Noise scales strongly with pixel size.…”

Section: Experimental Setup and Tests Descriptionmentioning

confidence: 99%

Problems in image target-based color correction

Gabriele¹,

Marco²,

Andrea³

et al. 2022

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This paper aims at presenting some problems that everyone could experience in the process of image target-based color correction (CC). We have acquired a set of images using a color checker, here we present some measures of these image before and after the color correction and we compare them with the actual values of the color checker. Comments about the results and their departures from the scene are reported together with the changes after color correction. It is shown how real scene acquisitions are subject to many issues that makes color correction process very far from the idealized colorimetric ideas.

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“…It has to be noted that the total noise value is a complex mixture of several noise sources of lens system, pixel size, sensor technology and manufacturing, image processing pipeline, ISO speed, exposure time, RAW conversion. Noise scales strongly with pixel size, becoming ugly in compact digital cameras and camera phones with tiny sensors, especially at high ISO speeds or in dim light, and affected by sensor technology and manufacturing quality (Peltoketo, 2015). The noise amount can be partially controlled by camera parameters, like ISO speed and exposure time, and denoising algorithms.…”

Section: Radiometric Processing Pipelinementioning

confidence: 99%

Evaluating Smartphones Color Fidelity and Metric Accuracy for the 3d Documentation of Small Artifacts

Gaiani

Apollonio

Fantini

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Smartphone camera technology has made significant improvements of sensors quality and software camera performance in recent years. Devices as Apple iPhone X and the Samsung Galaxy S9 Plus, allow to reach levels of image resolution, sharpness and color accuracy very close to prosumer SLR cameras, enabling also on-the-fly processing and procedures which were considered impossible to achieve until a few years ago. Starting from these premises, a series of issues and opportunities concerning smartphone application to artifacts documentation will be discussed. In particular, consistency and reliability of both shape and color representation achievable for small-medium artifacts belonging to exhibitions and museum collections. A low-cost, easy-to-use workflow based on low-cost widespread devices will be compared to consolidated digitization pipelines. The contribution focus is based on color accuracy of textured models achievable through smartphones by means of an internally developed application for the achievement of highly reliable developments of raw formats (.DNG) from Apple iPhone X. Color consistency will be calculated in terms of the mean camera chroma relative to the mean ideal chroma in the CIE color metric (&Delta;E*00) as defined in 2000 by the CIE on the CIEXYZ chromaticity diagram.

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Signal to Noise Ratio and Visual Noise of Mobile Phone Cameras

Cited by 4 publications

References 0 publications

Camera Dynamic Range Measurement: The Role of Lenses and Target Spatial Distribution

Camera Dynamic Range Measurement: The Role of Lenses and Target Spatial Distribution

Problems in image target-based color correction

Evaluating Smartphones Color Fidelity and Metric Accuracy for the 3d Documentation of Small Artifacts

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