Two-point nonuniformity correction based on LMS

Xing, Suxia; Zhang, Junju; Sun, Liling; Chang, Benkang; Qian, Yunsheng

doi:10.1117/12.566145

Cited by 13 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the augmented Lagrange equation, the constrained Equation ( 4) can be transformed into the unconstrained Equation (5).…”

Section: Problem Analysis Model Establishment and Solutionmentioning

confidence: 99%

See 1 more Smart Citation

CMOS Fixed Pattern Noise Elimination Based on Sparse Unidirectional Hybrid Total Variation

Zhang

et al. 2020

Sensors

View full text Add to dashboard Cite

With the improvement of semiconductor technology, the performance of CMOS Image Sensor has been greatly improved, reaching the same level as that of CCD in dark current, linearity and readout noise. However, due to the production process, CMOS has higher fix pattern noise than CCD at present. Therefore, the removal of CMOS fixed pattern noise has become the research content of many scholars. For current fixed pattern noise (FPN) removal methods, the most effective one is based on optimization. Therefore, the optimization method has become the focus of many scholars. However, most optimization models only consider the image itself, and rarely consider the structural characteristics of FPN. The proposed sparse unidirectional hybrid total variation (SUTV) algorithm takes into account both the sparse structure of column fix pattern noise (CFPN) and the random properties of pixel fix pattern noise (PFPN), and uses adaptive adjustment strategies for some parameters. From the experimental values of PSNR and SSM as well as the rate of change, the SUTV model meets the design expectations with effective noise reduction and robustness.

show abstract

“…According to the augmented Lagrange equation, the constrained Equation ( 4) can be transformed into the unconstrained Equation (5).…”

Section: Problem Analysis Model Establishment and Solutionmentioning

confidence: 99%

“…Calibration-based methods have the characteristics of simple calculation and high correction accuracy, and are widely used in engineering applications. The most commonly used method is the two-point calibration method [ 4 , 5 ]. The corresponding photoelectric curves of CIS show a certain degree of non-linearity.…”

Section: Introductionmentioning

confidence: 99%

CMOS Fixed Pattern Noise Elimination Based on Sparse Unidirectional Hybrid Total Variation

Zhang

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…6 If an overall systematic response model is the goal, the NUC methods are often associated with calibration, adaptive filtering or other methods for estimating system response parameters. 8–30 Imaging system response nonuniformity models and methods for representation are essential for NUC and nonuniformity evaluation (NUE), and research on these topics is the basis of system response NUC and NUE. However, some parameters drift over time; hence, the representation of imaging system response nonuniformity is difficult.…”

Section: Introductionmentioning

confidence: 99%

Response nonuniformity modelling for colour imaging systems

Xie

Sun

Gong

et al. 2023

Lighting Research & Technology

View full text Add to dashboard Cite

In this paper, a theoretical analysis reveals that system radiation transmission nonuniformity and system radiation conversion nonuniformity have different forms. A colour imaging system response nonuniformity model is then proposed according to the two kind of nonuniformity of three channels. The model includes two models, one for brightness and one for chromaticity. The brightness model is built according to the nonuniformity of single channel. The chromaticity model is built as an error ellipse in the chromaticity diagram. The error ellipse can be also used as a representation parameter of the radiation conversion nonuniformity. The proposed models were verified using three commercial digital cameras. The experimental results show that the proposed nonuniformity model is correct. Moreover, the proposed representation parameter is an effective way to evaluate and characterize the nonuniformity of a colour imaging system. This research has value as a reference for the correction and evaluation of response nonuniformity in colour imaging systems.

show abstract

“…There are two kinds of non-uniformity correction (NUC) methods for imaging systems. One is calibration-based method 1–15 and the other is scene-based NUC method. 16–44 The NUC model is the most important factor in both methods.…”

Section: Introductionmentioning

confidence: 99%

Colour imaging system response non-uniformity correction based on inverse model and regularization method

Xie

Sun

Gong

et al. 2022

Lighting Research & Technology

View full text Add to dashboard Cite

The nonlinear response affects the effect of imaging system response non-uniformity correction (NUC) methods. Most of the methods are effective in a certain range of responses. In this paper, a new NUC method is proposed based on the mechanism of imaging system response non-uniformities production. Optical system-related non-uniformity is described as radiation transmission non-uniformity (RTNU) and detector-related non-uniformity is described as radiation conversion non-uniformity (RCNU). The RTNU is removed by inverse operation and RCNU is removed by regularization optimization. We verify the proposed method with respect to visual effect evaluation of actual scene images and three performance metrics evaluation of statistical F ratio, F-norm roughness and chromatic aberration ellipse. The experimental results verify the effect of our method. The proposed method is effective for NUC in a larger range of responses.

show abstract

Two-point nonuniformity correction based on LMS

Cited by 13 publications

References 0 publications

CMOS Fixed Pattern Noise Elimination Based on Sparse Unidirectional Hybrid Total Variation

CMOS Fixed Pattern Noise Elimination Based on Sparse Unidirectional Hybrid Total Variation

Response nonuniformity modelling for colour imaging systems

Colour imaging system response non-uniformity correction based on inverse model and regularization method

Contact Info

Product

Resources

About