The Geometry of Noise in Color and Spectral Image Sensors

Clouet, Axel; Vaillant, Jacques; Alleysson, David

doi:10.3390/s20164487

Cited by 5 publications

(2 citation statements)

References 34 publications

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“…With the introduction of a tolerance in the computation of paramer sets, the choice of this value becomes important. As mentioned in the introduction, it can be directly related to JNDs or noise, such as measurement or repeatability noise -both in magnitude and geometry (Clouet, 2020). For example, typical spectrophotometers can have a measurement repeatability of between 0.01 to 0.1 ∆E2000 -meaning that measuring the same surface multiple times.…”

Section: Results and Examplesmentioning

confidence: 99%

Real World Metamer Sets: Or How we Came to Love Noise

Morovic¹,

Morovič²

2021

cic

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It is well known that color formation acts as a noise-reducing lossy compression mechanism that results in ambiguity, known as metamerism. Surfaces that match under one set of conditions-an illuminant and observer or capture device-can mismatch under others. The phenomenon has been studied extensively in the past, leading to important results like metamer mismatch volumes, color correction, reflectance estimation and the computation of metamer sets-sets of all possible reflectances that could result in a given sensor response. However, most of these approaches have three limitations: first, they simplify the problem and make assumptions about what reflectances can look like (i.e., being smooth, natural, residing in a subspace based on some measured data), second, they deal with strict mathematical metamerism and overlook noise or precision, and third, only isolated responses are considered without taking the context of a response into account. In this paper we address these limitations by outlining an approach that allows for the robust computation of approximate unconstrained metamer sets and exact unconstrained paramer sets. The notion of spatial or relational paramer sets that take neighboring responses into account, and applications to illuminant estimation and color constancy are also briefly discussed.

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Section: Results and Examplesmentioning

confidence: 99%

Real World Metamer Sets: Or How we Came to Love Noise

Morovic¹,

Morovič²

2021

cic

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“…In color images, amplification happens mostly on the blue color channel than that of red and green. Hence, more amplifier noise can be found in the blue channel [15]. In an image sensor, the amplifier is the major type of noise with Gaussian distribution and is consistently found in the dark areas of an image [14].…”

Section: Introductionmentioning

confidence: 99%

A Study on Various Common Denoising Methods on Chest X-ray Images

Chattopadhyay¹

2022

Artificial Intelligence Evolution

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Image 'denoising' is an important pre-processing step as noise affects the image quality. The behaviors of denoising algorithms have been examined on a set of 2D Chest X-ray (CXR) images. Both the 'Linear' and 'non-Linear' denoising methods are considered, each having two techniques, such as (i) Moving average and (ii) Gaussian under the Linear method, and (iii) Median and (iv) Bilateral under the non-Linear method, respectively. Noise variance and Signal-to-Noise Ratio (SNR) are computed on the raw images. The study finds that, Median filter is the best of the lot with the PSNR mean = 34.5213; PSNR σ = 0.9618; MSE mean = 12.2337; MSE σ = 1.5491; and Big(O) = 0.02873 milliseconds. Finally, a comparative study has been made among these denoising methods to predict five hundred Tubercular CXRs, which shows that, using the Median filter, 92% CXRs can be accurately diagnosed, followed by Gaussian, Bilateral, and Moving average type filters with the respective accuracies of 80%, 72%, and 60%, respectively. This work could be a ready-reckoner to the researchers in choosing the best filtering technique when working on Medical X-ray images.

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Dual Chalcogen‐Bonding Interaction for High‐Performance Filterless Narrowband Organic Photodetectors

Kim,

Yun

et al. 2024

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A novel green‐absorbing organic molecule featuring dual intramolecular chalcogen bonds is synthesized and characterized. This molecule incorporates two such bonds: one between a tellurium atom and the oxygen atom of a carbonyl moiety, and the other between the tellurium atom and the adjacent nitrogen atom within a pyridine moiety. The molecule, featuring dual intramolecular chalcogen bonds exhibits a narrow absorption spectrum and elevated absorption coefficients, closely aligned with a resonance parameter of approximately 0.5. This behavior is due to its cyanine‐like characteristics and favorable electrical properties, which are a direct result of its rigid, planar molecular structure. Therefore, this organic molecule forming dual intramolecular chalcogen bonds achieves superior optoelectronic performance in green‐selective photodetectors, boasting an external quantum efficiency of over 65% and a full‐width at half maximum of less than 95 nm while maintaining the performance after 1000 h of heating aging at 85 °C. Such organic photodetectors are poised to enhance stacked organic photodetector‐on‐silicon hybrid image sensors, paving the way for the next‐generation of high‐resolution and high‐sensitivity image sensors.

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The Geometry of Noise in Color and Spectral Image Sensors

Cited by 5 publications

References 34 publications

Real World Metamer Sets: Or How we Came to Love Noise

Real World Metamer Sets: Or How we Came to Love Noise

A Study on Various Common Denoising Methods on Chest X-ray Images

Dual Chalcogen‐Bonding Interaction for High‐Performance Filterless Narrowband Organic Photodetectors

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