Scanning Modulation Transfer Function Model of TDI CMOS Image Sensor

Nie, Kaiming; Liu, Lin; Yao, Suying; Xu, Jiangtao

doi:10.1007/s11265-015-0975-7

Cited by 4 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TDI-CIS is mainly comprised of a pixel array, column-parallel accumulators and column-parallel analog-to-digital converters (ADCs). In Figure 1 , a block diagram of TDI-CIS is depicted [ 16 ]. The scanning direction of TDI is called “along-track direction”, and the direction which is orthogonal to the along-track direction is called “across-track direction”.…”

Section: Analysis and Modeling Of Sensor Noisementioning

confidence: 99%

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor

Liu

Wang

et al. 2015

Sensors

Self Cite

View full text Add to dashboard Cite

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

show abstract

Section: Analysis and Modeling Of Sensor Noisementioning

confidence: 99%

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor

Liu

Wang

et al. 2015

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System

Gao,

Zheng,

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

The camera response function (CRF) establishes a numerical mapping between focal plane radiance, camera imaging parameters, and the intensity of output images. It plays a significant role in areas such as high dynamic range imaging and image processing. To establish an accurate response model for time delay integration (TDI) complementary metal-oxidesemiconductor (CMOS) imaging systems, this paper proposes a radiometric calibration method for TDI CMOS imaging systems based on complex real-world scene images. The study begins by conducting an extensive analysis of the data link within the TDI CMOS imaging system, which serves as the foundation for establishing its a priori theoretical response model. Subsequently, the problem of solving the CRF model is transformed into an overdetermined equation established through the least square method. The optimal solution for this equation is obtained by singular value decomposition (SVD), which leads to the derivation of a three-dimensional response function for the imaging system. Finally, under consistent optical radiation conditions, radiation calibration experiments are performed on various targets using a self-developed TDI CMOS imaging system. The CRF is obtained based on the captured experimental image data. Furthermore, this paper's approach is compared with the widely adopted linear fitting method commonly used within the respective field. The experimental results show that the visually perceived quality, structural similarity, mean grayscale, mean gradient, entropy, and standard deviation of images synthesized using the CRF proposed in this paper are closer to those of actual captured images. The proposed method demonstrates higher accuracy and can provide a reliable basis for applications such as radiation response calibration of on-orbit spaceborne payloads, selection of imaging parameters, and multi-exposure fusion of remote sensing images.

show abstract

Hyper-Temporal Data Based Modulation Transfer Functions Compensation for Geostationary Remote Sensing Satellites

Yang

Liang

et al. 2022

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Scanning Modulation Transfer Function Model of TDI CMOS Image Sensor

Cited by 4 publications

References 13 publications

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor

Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System

Hyper-Temporal Data Based Modulation Transfer Functions Compensation for Geostationary Remote Sensing Satellites

Contact Info

Product

Resources

About