Imaging System Response Linearization And Shading Correction

Dinstein, I.; Merkle, F.; Lam, Tinwai; Wong, Kwan Y.

doi:10.1117/12.7973384

Cited by 9 publications

(3 citation statements)

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“…The performance of low precision analog to digital converters were improved by Frey and Loeliger using a look-up table approach [8]. Efforts were made by Dinstein et al to perform a LUT linearization for imaging systems [9]. The authors carried out a subtraction for dark current noise and then applied a LUT that was obtained by fitting the measured system response to an analytical curve.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Do-It-Yourself LUT-based Linearization of Image Sensors

Czech,

Trumpy,

Syed

2023

archiving

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Imaging sensors are linear over a large part of their operational range. Nevertheless, their behavior becomes nonlinear when approaching saturation. This is undesired if such sensors are used for scientific measurements. In this work, a simple and efficient off-chip method is proposed for image sensor linearization. First, the sensor response is characterized with a constant irradiance and a sequence of captures at several integration times. Then a 1D look-up table is calculated to compensate for the nonlinear range. This LUT can be applied to the raw sensor data before further postprocessing. The higher signal-to-noise ratio of captured data is used to demonstrate the benefit of the extended linear range. The proposed method can restore linearity while being easy to implement and computationally efficient.

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Section: Introduction and Related Workmentioning

confidence: 99%

Do-It-Yourself LUT-based Linearization of Image Sensors

Czech,

Trumpy,

Syed

2023

archiving

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“…Vignetting distortion of an optical system has a significant effect on the results of image mosaic [2,6], automatic thresholding, and more importantly, quality image acquisition such as image, video quality enhancement [1,3,7,9], and direct digitization of a painting [4].…”

Section: Introductionmentioning

confidence: 99%

“…There are various research efforts to deal with vignetting distortion problem [1][2][3][4]6,7,9]. The most obvious approach for vignetting correction begins by setting up a uniform white illumination over a reference object in order to find intensity profile distribution of an optical system in question [10].…”

Section: Introductionmentioning

confidence: 99%

Vignetting distortion correction method for high quality digital imaging

Chung

Soh

2004

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.

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Vignetting refers to a position dependent loss of light in the output of an optical system causing gradual fading out of an image near the periphery. In this paper, we propose a method for correcting vignetting distortion by introducing nonlinear model fitting of a proposed vignetting distortion function. The proposed method aims for embedded digital imaging applications as well as conventional image enhancement. We could obtain a light intensity profile distribution without precisely controlled illumination and considerably reduce memory requirement for vignetting correction compared with traditional lookup table (LUT) methods. We show the effectiveness of the proposed method by presenting experimental results obtained from commercial digital cameras.

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Nonvision Sensors, Range Finders, and Processing

Browne

Norton–Wayne

1986

Vision and Information Processing for Automation

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Imaging System Response Linearization And Shading Correction

Cited by 9 publications

References 0 publications

Do-It-Yourself LUT-based Linearization of Image Sensors

Do-It-Yourself LUT-based Linearization of Image Sensors

Vignetting distortion correction method for high quality digital imaging

Nonvision Sensors, Range Finders, and Processing

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