Fixed Pattern Noise Research Articles

High Consistency Ramp Design Method for Low Noise Column Level Readout Chain.

In order to address the inconsistency problem caused by parasitic backend wiring among multiple ramp generators and among multiple columns in large-array CMOS image sensors (CIS), this paper proposes a high-precision compensation technology combining average voltage technology, adaptive negative feedback dynamic adjustment technology, and digital correlation double sampling technology to complete the design of an adaptive ramp signals inconsistency calibration scheme. The method proposed in this article has been successfully applied to a CIS with a pixel array of 8192(H) × 8192(V), based on the 55 nm 1P4M CMOS process, with a pixel size of 10×10μm2. The chip area is 88(H) × 89(V) mm2, and the frame rate is 10 fps. The column-level analog-to-digital converter is a 12-bit single-slope analog-to-digital converter (SS ADC). The experimental results show that the ramp generation circuit proposed in this paper can reduce the inconsistency among the ramp signals to 0.4% LSB, decreases the column fixed pattern noise (CFPN) caused by inconsistent ramps of each column to 0.000037% (0.15 e-), and increases the overall chip area and power consumption by only 0.6% and 0.5%, respectively. This method provides an effective solution to the influence of non-ideal factors on the consistency of ramp signals in large area array CIS.

Column fixed-pattern noise removal in solar images using two-way filtering

Column fixed-pattern noise removal in solar images using two-way filtering

Noise suppression in pulsed IR thermographic NDT: Efficiency of data processing algorithms

Various types of noise, which accompany active TNDT procedures using optical heating, have been analyzed, both numerically and experimentally. An emphasis has been made on the suppression of surface clutter, which represents local areas of varying absorptivity/emissivity. The concept of signal-to-noise that is typically used in defect detection has been applied to fixed pattern noise in order to compare capabilities of data processing algorithms in reducing surface clutter. The experimental investigation has been fulfilled on a special sample containing both subsurface air-filled defects and areas with varying emissivity/absorptivity. The best suppression of the fixed pattern noise was provided by the complex wavelet transform and principle component analysis. Because of 3D heat diffusion, clutter spot boundaries are often underlined by particular data processing algorithms thus producing specific contours. The test situations where subsurface defects are located under localized clutter spots have been analyzed to demonstrate an overshadowing effect of such spots when detecting hidden defects.

Development and validation of a 64-channel ROIC prototype for SWIR line scan sensor applications

This paper introduces the development and validation of a 64-channel readout integrated circuit (ROIC) prototype, specifically engineered for short-wave infrared (SWIR) line scan sensors. The design of the prototype undergoes various evaluation through comprehensive silicon-level testing, ensuring its robust performance across a variety of operational modes. Key features such as capacitive transimpedance amplifier (CTIA) gain control and sensitivity control are examined, demonstrating the prototype's ability to handle different input currents and capacitance values with precision. Fabricated with 0.18-μm CMOS technology, the ROIC is tailored for integration with Indium Gallium Arsenide (InGaAs) pixels, facilitating high-resolution imaging. The prototype consumes 26.55 mW with A 3.3 V power supply. The fabricated chip show that the total random noise (RN) level is 128 μVrms and column fixed pattern noise (FPN) is 0.16 mVrms

Scene-based dual domain non-uniformity correction algorithm for stripe and optics-caused fixed pattern noise removal

Non-uniformity is a long-standing problem that significantly degrades infrared images through fixed pattern noise (FPN). Existing scene-based algorithms for non-uniformity correction (NUC) effectively eliminate stripe FPN assuming consistent inter-frame non-uniformity. However, they are ineffective in handling spatially continuous optical FPN. In this paper, a scene-based dual domain correction approach is proposed to address the non-uniformity problem by simultaneously removing stripe and optics-caused FPN. We achieve this through gain correction in the frequency domain and offset correction in the spatial domain. To remove stripes, we approximate the desired image using a guided filter and iteratively update the bias correction parameters frame by frame. For optics-caused noise removal, we separate low frequency noise from the scene using Fourier transform and update the gain correction parameters accordingly. To mitigate ghost artifacts, a combined strategy is introduced to adaptively adjusts learning rates and weights during the updating stage. Comprehensive evaluations demonstrate that our proposed approach outperforms compared methods in both real and simulated non-uniformity infrared videos.

Balancing the Efficiency and Sensitivity of Defect Inspection of Non-Patterned Wafers with TDI-Based Dark-Field Scattering Microscopy.

In semiconductor manufacturing, defect inspection in non-patterned wafer production lines is essential to ensure high-quality integrated circuits. However, in actual production lines, achieving both high efficiency and high sensitivity at the same time is a significant challenge due to their mutual constraints. To achieve a reasonable trade-off between detection efficiency and sensitivity, this paper integrates the time delay integration (TDI) technology into dark-field microscopy. The TDI image sensor is utilized instead of a photomultiplier tube to realize multi-point simultaneous scanning. Experiments illustrate that the increase in the number of TDI stages and reduction in the column fixed pattern noise effectively improve the signal-to-noise ratio of particle defects without sacrificing the detecting efficiency.

Explosive Growth of Image Sensors in Smart Government Technology and Economic Scale

CMOS image sensor is a rapidly developing image sensor product in the past decade. Relying on the advantages of process compatibility with standard CMOS process, CMOS image sensor integrates analog photoelectric photosensitive circuit and digital signal processing circuit to become a small and powerful system on chip. This article mainly studies the explosive growth of image sensors in smart government technology and economic scale. The main purpose of this article is to study the technical application of image sensors, reduce the administrative cost of social governance, improve the level of government governance, benefit the public, and realize the requirements of smart government affairs and rapid economic development of the city. This study tested the static performance of the analog-to-digital conversion circuit by inputting a limited number of sampling points, and its integral nonlinearity and differential nonlinearity were both less than 1LSB. The bandgap reference circuit provides a reference level for the entire system. It uses two PNP-type bipolar transistors parasitic in the CMOS process to achieve a temperature and voltage-independent bandgap reference voltage through the feedback of the operational amplifier. It is ideal for use In the case of resistance simulation, its accuracy reaches 16.6ppm. The scanning method of the pixel array uses multi-sampling technology to increase the dynamic range of the sensor by 2N times. The correlated sub-sampling technology eliminates the fixed pattern noise between pixel units. The use of pipelined analog-to-digital converters can achieve good resolution, speed and area compromise.Through the realization and simulation of transistor-level circuits, the performance of each part of the system meets the requirements of design and application.

Degradation analysis of the pinned photodiode CMOS image sensors induced by energetic proton radiation

The experiments of the 0.18-μm pinned photodiode (PPD) CMOS image sensors (CISs) irradiated by energetic proton radiation with energies of 20, 40, 60, and 100 MeV are presented. The degradations of the mean dark signal, dark signal non-uniformity (DSNU), and fixed pattern noise (FPN) induced by protons are presented. The experimental results show that the mean dark signal degradations of the CISs decrease with increasing proton energy at the same fluence. The degradations induced by proton radiation at different fluence are also presented. The mean dark signals increase with increasing integration time at the same proton fluence. The degradation mechanisms of the CISs induced by energetic protons are analyzed.

Rheological engineering of perovskite suspension toward high-resolution X-ray flat-panel detector

Solution-processed polycrystalline perovskite film is promising for the next generation X-ray imaging. However, the spatial resolution of current perovskite X-ray panel detectors is far lower than the theoretical limit. Herein we find that the pixel level non-uniformity, also known as fixed pattern noise, is the chief culprit affecting the signal-to-noise ratio and reducing the resolution of perovskite detectors. We report a synergistic strategy of rheological engineering the perovskite suspensions to achieve X-ray flat panel detectors with pixel-level high uniformity and near-to-limit spatial resolution. Our approach includes the addition of methylammonium iodide and polyacrylonitrile to the perovskite suspension, to synergistically enhance the flowability and particle stability of the oversaturated solution. The obtained suspension perfectly suits for the blade-coating process, avoiding the uneven distribution of solutes and particles within perovskite films. The assembled perovskite panel detector exhibits greatly improved fixed pattern noise value (1.39%), high sensitivity (2.24 × 104 μC Gyair−1 cm−2), low detection limit (28.57 nGyair·s−1) as well as good working stability, close to the performance of single crystal detectors. Moreover, the detector achieves a near-to-limit resolution of 0.51 lp/pix.

Fixed Pattern Noise Removal Based on a Semi-Calibration Method.

Due to the manufacturing imperfections, nonuniformities are ubiquitous in digital sensors, causing the notorious Fixed Pattern Noise (FPN). The ability of modern digital cameras to take images under low-light environments is severely limited by the FPN. This paper proposes a novel semi-calibration-based method for the FPN removal that utilizes a pre-calibrated Noise Pattern. The key observation of this work is that the FPN in each shot is actually a scaled Noise Pattern with an unknown scale parameter, since each pixel in the array generates a characteristic amount of dark current which is fundamentally determined by its physical properties. Given a noised image and the corresponding Noise Pattern, the scale parameter is automatically estimated, and then the FPN is removed by subtracting the scaled Noise Pattern from the noised image. The estimation of the scale parameter is based on an entropy minimization estimator, which is derived from the Maximum Likelihood principle and is further justified by subsequent analysis that minimizing the entropy uniquely identifies the true parameter. Convergence issues, as well as the optimality of the proposed estimator, are also theoretically discussed. Finally, some applications are given, illustrating the performance of the proposed FPN removal method in real-world tasks.

Thermal imaging spatial noise removal via deep image prior and step-variable total variation regularization

The imaging quality of an uncooled long wave infrared camera suffers severely from time-drifted spatial noises if not regulated by a thermoelectric cooler (TEC). These noises can be categorized within the frequency domain as either fixed pattern noise (FPN) or low-frequency noise (LPN). The time-drifted FPN is primarily governed by the temperature fluctuations of the focal plane array (FPA), whereas the LPN predominantly originates from non-uniform background radiations. Most existing methods have been proposed to address the FPN or LPN independently rather than from a unified perspective. In this paper, a self-supervised convolution neural network (CNN) is proposed to remove these two types of noise simultaneously. Because of the combination of the deep image prior (DIP) architecture and the total variation (TV) regularizer, this method is named TV-DIP. With the assumption that the spatial noises are constant in a short period of time, the spatial noise pattern is extracted directly from multiple continuous raw frames without ground-truth noise-free images. In this way, the noise pattern can be updated periodically during running time, without requiring the use of a mechanical shutter. Besides, the original TV regularizer is extended with a variable step, which shows a significant enhancement on the LPN denoising task. Furthermore, both simulation and experimental results have demonstrated that this approach achieves better performance in terms of the removal of spatial noise, the preservation of detail, and the suppression of artifacts. The source code and dataset are available on the website: https://github.com/brunolinux/TV-DIP

A Comprehensive Methodology for Optimizing Read-Out Timing and Reference DAC Offset in High Frame Rate Image Sensing Systems.

This paper presents a comprehensive timing optimization methodology for power-efficient high-resolution image sensors with column-parallel single-slope analog-to-digital converters (ADCs). The aim of the method is to optimize the read-out timing for each period in the image sensor's operation, while considering various factors such as ADC decision time, slew rate, and settling time. By adjusting the ramp reference offset and optimizing the amplifier bandwidth of the comparator, the proposed methodology minimizes the power consumption of the amplifier array, which is one of the most power-hungry circuits in the system, while maintaining a small color linearity error and ensuring optimal performance. To demonstrate the effectiveness of the proposed method, a power-efficient 108 MP 3-D stacked CMOS image sensor with a 10-bit column-parallel single-slope ADC array was implemented and verified. The image sensor achieved a random noise of 1.4 e-rms, a column fixed-pattern noise of 66 ppm at an analog gain of 16, and a remarkable figure-of-merit (FoM) of 0.71 e-·nJ. The sensor utilized a one-row read-out time of 6.9 µs, an amplifier bandwidth of 1.1 MHz, and a reference digital-to-analog converter (DAC) offset of 512 LSB. This timing optimization methodology enhances energy efficiency in high-resolution image sensors, enabling higher frame rates and improved system performance. It could be adapted for various imaging applications requiring optimized performance and reduced power consumption, making it a valuable tool for designers aiming to achieve optimal performance in power-sensitive applications.

Fixed-pattern noise model for filters in uncooled infrared focal plane array imaging optical paths

In recent years, uncooled infrared focal plane arrays (IRFPAs) have gained importance in the field of industrial gas leak detection; however, their applications often require the inclusion of narrow-band filters in the infrared objective lenses to limit the range of incident radiation, which, in turn, produces fixed-pattern noise that affects imaging quality. To this end, this study investigates the fixed-pattern noise model of uncooled IRFPA imaging considering the influence of filters and adopts the theory of the radiation conversion angle coefficient to establish a model of the fixed-pattern noise distribution formed by the filter’s, reflected, and stray radiations from the optical path environment on the IRFPA surface. Theoretical analysis and test results demonstrate that both results are basically consistent. Notably, the results of this study have a guiding meaning for the gas leak uncooled infrared imaging detection system for targeted non-uniformity correction, and have application value for improving the detection efficiency of the detection system.

A high-speed transient waveform sampling SCA ASIC prototype in 180 nm CMOS technology

Switched capacitor array (SCA) is an important method of waveform digitization in high-energy physics experiments. This paper presents the design and test results of an eight-channel SCA ASIC for high-speed waveform sampling. The ASIC is designed and fabricated in 180 nm CMOS technology. The sampling rate of up to 14.25 Gsps is achieved by adopting the proposed dual-chain interpolating delay cell in DLL. The ASIC can be configured to operate in two modes: long-chain mode for deeper sampling depth and ping-pong mode for recording two waveforms in a short time. The bandwidth is over 1.1 GHz. By optimizing the sampling order, the distortion caused by the bandwidth discontinuity is reduced. Deep N-well is adopted to isolate the interference between digital and analog signals. The test results show that the random noise is approximately 0.87 mV RMS after the fixed-pattern noise correction. The time resolution is better than 5 ps RMS over the time measurement range of approximately 73μs.

Optimizing the sensitivity of high repetition rate broadband transient optical spectroscopy with modified shot-to-shot detection

A major limitation of transient optical spectroscopy is that relatively high laser fluences are required to enable broadband, multichannel detection with acceptable signal-to-noise levels. Under typical experimental conditions, many condensed phase and nanoscale materials exhibit fluence-dependent dynamics, including higher order effects such as carrier–carrier annihilation. With the proliferation of commercial laser systems, offering both high repetition rates and high pulse energies, have come new opportunities for high sensitivity pump-probe measurements at low pump fluences. However, experimental considerations needed to fully leverage the statistical advantage of these laser systems have not been fully described. Here, we demonstrate a high repetition rate, broadband transient spectrometer capable of multichannel shot-to-shot detection at 90 kHz. Importantly, we find that several high-speed cameras exhibit a time-domain fixed pattern noise resulting from interleaved analog-to-digital converters, which is particularly detrimental to the conventional “ON/OFF” modulation scheme used in pump-probe spectroscopy. Using a modified modulation and data processing scheme, we achieve a noise level of 10−5 in 4 s for differential transmission, an order of magnitude lower than for commercial 1 kHz transient spectrometers for the same acquisition time. We leverage the high sensitivity of this system to measure the differential transmission of monolayer graphene at low pump fluence. We show that signals on the order of 10−6 OD can be measured, enabling a new data acquisition regime for low-dimensional materials.

Infrared Image Deconvolution Considering Fixed Pattern Noise.

As the demand for thermal information increases in industrial fields, numerous studies have focused on enhancing the quality of infrared images. Previous studies have attempted to independently overcome one of the two main degradations of infrared images, fixed pattern noise (FPN) and blurring artifacts, neglecting the other problems, to reduce the complexity of the problems. However, this is infeasible for real-world infrared images, where two degradations coexist and influence each other. Herein, we propose an infrared image deconvolution algorithm that jointly considers FPN and blurring artifacts in a single framework. First, an infrared linear degradation model that incorporates a series of degradations of the thermal information acquisition system is derived. Subsequently, based on the investigation of the visual characteristics of the column FPN, a strategy to precisely estimate FPN components is developed, even in the presence of random noise. Finally, a non-blind image deconvolution scheme is proposed by analyzing the distinctive gradient statistics of infrared images compared with those of visible-band images. The superiority of the proposed algorithm is experimentally verified by removing both artifacts. Based on the results, the derived infrared image deconvolution framework successfully reflects a real infrared imaging system.

Estimation of Camera’s Noise by Uniform Target Segmentation

This article proposes a method for evaluating digital camera noise. The method allows to estimate all four noise components: light and dark fixed-pattern (spatial) and temporal noise. We need to register only two scenes: dark and uniform light. Dark spatial and dark temporal noise is measured from two dark frames. Light temporal and light spatial noise is estimated from two light frames using automatic segmentation of a uniform target (ASUT). Noise of visible range (silicon) cameras of four types was measured: consumer Canon EOS M100, machine vision PixeLink PL-B781F, microscope Retiga R6, and scientific MegaPlus II ES11000. Obtained noise values are equal to that ones for the EMVA Standard 1288 within the value spread. The difference is 0.1% (dark temporal), 1.0% (dark spatial), 1.3% (light spatial), and 2.5% (light temporal) only. The proposed method provides a fast and accurate camera noise estimation. This can be used to improve information quality and speed of light registration systems.

Modified Two-Point Correction Method for Wide-Spectrum LWIR Detection System.

Non-uniformity commonly exists in the infrared focal plane, which behaves as the fixed-pattern noise (FPN) and seriously affects the image quality of long-wave infrared (LWIR) detection systems. The two-point correction (TPC) method is commonly used to reduce image FPN in engineering. However, when a wide-spectrum LWIR detection system calibrated with a black body is used to detect weak and small targets in the sky, FPN still appears in the image, affecting its uniformity. The effects of atmospheric transmittance characteristics of long-range paths on the non-uniformity of wide-spectrum long-wave infrared systems have not been studied. This paper proposes a modified TPC model based on spectral subdivision that introduces atmospheric transmittance. Additionally, the effects of atmospheric transmittance characteristics on the long-wave infrared non-uniform correction coefficient are analyzed. The experimental results for a black body scene and sky scene using a weak and small target detection system with a long-wave Sofradir FPA demonstrate that the wide-spectrum LWIR detection system fully considers atmospheric transmittance when performing calibration based on the TPC method, which can reduce the non-uniformity of the image.

Infrared Image Pre-Processing and IR/RGB Registration with FPGA Implementation

Infrared imaging sensors are frequently used in thermal signature detection applications in industrial, automotive, military and many other areas. However, advanced infrared detectors are generally associated with high costs and complexity. Infrared detectors usually necessitate a thermoelectric heater–cooler for temperature stabilization and various computationally complex preprocessing algorithms for fixed pattern noise (FPN) correction. In this paper, we leverage the benefits of uncooled focal plane arrays and describe a complete digital circuit design for Field Programmable Gate Array (FPGA)-based infrared image acquisition and pre-processing. The proposed design comprises temperature compensation, non-uniformity correction, defective pixel correction cores, spatial image transformation and registration with RGB images. When implemented on Xilinx Ultrascale+ FPGA, the system achieves a throughput of 30 frames per second using the Fraunhofer IMS Digital 17 μm QVGA-IRFPA with a microbolometer array size of 320 × 240 pixels and an RGB camera with a 1024 × 720 resolution. The maximum ratio of the standard deviation to the mean of 0.35% was achieved after FPN correction.

FPN Modeling and Model-Based Correction for Shutter-Less Uncooled Bolometric Imagers

This article establishes a behavior model for analyzing the temperature-dependent fixed pattern noise (TD-FPN) induced by pixel passive and active resistance for uncooled bolometric thermal imagers. A model-based two-point correction method is also proposed to compensate for the TD-FPN by using the ratio of passive and active resistance. An infrared imaging system based on a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$640\times512$ </tex-math></inline-formula> readout chip is implemented to verify the proposed model and the model-based correction method. The comparison between the simulation and measurement results shows the model’s accuracy. The residuals after the model-based correction are within ±25 LSBs, which is considerably lower than the traditional method’s residuals. Due to the low residuals, the spatial noise equivalent temperature difference (S-NETD) is less than 100 mK within the temperature range of [−40 °C to 80 °C]. The proposed model and the correction method enable uncooled bolometric thermal imagers to achieve low-cost and wide-temperature-range shutter-less operation.