29 results about "Fixed-pattern noise" patented technology

Disclosed herein are fixed pattern noise (FPN) reduction techniques in image sensors operated with pulsed illumination. In one embodiment, a method includes, during a first sub-exposure period of a frame, (a) operating a first tap of a pixel to capture a first signal corresponding to a first charge at a first floating diffusion, the first charge corresponding to a first light incident on a photosensor, and (b) operating a second tap of the pixel to capture a first parasitic signal corresponding to FPN at a second floating diffusion. The method further includes, during a second sub-exposure period of the frame, (a) operating the second tap to capture a second signal corresponding to a second charge at the second floating diffusion, the second charge corresponding to a second light incident on the photosensor, and (b) operating the first tap to capture a second parasitic signal corresponding to FPN at the first floating diffusion.

The invention provides an infrared image non-uniformity correction method, image processing equipment and a storage medium, and the method comprises the steps: subtracting estimated global fixed pattern noise from a current observation frame, obtaining a preliminary correction image, carrying out the analysis and calculation of local fixed pattern noise based on continuous multiple frames of preliminary correction images, and carrying out the secondary filtering of the local fixed pattern noise. According to the two-stage processing mechanism, the observation image is corrected based on the inherent global fixed pattern noise of the infrared focal plane array and the local fixed pattern noise generated due to scene change, time consistency and space difference are considered, and the fixed pattern noise is effectively removed. According to the method, extra calibration is not needed, the fixed pattern noise can be stably extracted, the dynamic self-adaptive capability is achieved, and the quality and usability of the infrared image in a complex environment are improved.

This application provides a signal processing device, image sensor, electronic device, and signal processing method, relating to the field of sensor technology. It improves column fixed-pattern noise in image sensors and enhances image quality. Specifically, the signal processing device includes a switching module, a switching decoder, a multiplexer, and multiple signal conversion modules. Multiple input terminals of the switching module are coupled one-to-one with multiple pixel circuits; multiple output terminals of the switching module are coupled one-to-one with the input terminals of the multiple signal conversion modules; the control terminal of the switching module is coupled with the output terminal of the switching decoder; and the input terminal of the switching decoder is coupled with a timing controller. The output terminals of the multiple signal conversion modules are coupled one-to-one with the multiple input terminals of the multiplexer; the output terminal of the multiplexer is used to output the quantized pixel signal. This application embodiment describes the process of reading out the pixel signal.

The invention discloses a photovoltaic cell photoluminescence image noise identification and suppression method and system, and relates to the technical field of photovoltaic cell defect detection.The method comprises the steps that photoluminescence images of a photovoltaic cell under dark field and bright field conditions are collected through an image sensor; pre-processing the image, wherein the pre-processing comprises blind pixel correction based on a manual calibration method and black level correction based on absolute difference operation; based on the preprocessed image, fixed pattern noise is identified through a multi-frame comparison technology, and a noise position mapping matrix is generated; and based on the matrix, carrying out noise suppression on the image by adopting a selective multi-stage median filtering strategy, and outputting a corrected image. According to the method, the problems of image quality reduction and low defect identification precision caused by fixed-mode noise interference in the prior art are effectively solved, efficient processing and detail reservation are taken into account, and the accuracy and reliability of photovoltaic cell defect detection are remarkably improved.

A nuclear-grade radiation-resistant infrared video monitoring system belongs to the technical field of nuclear facility safety monitoring, and comprises a radiation-resistant infrared camera used for collecting infrared video data in a strong nuclear radiation environment; the image processing unit is used for performing enhancement processing on the infrared video data, removing non-uniform fixed mode noise caused by radiation and obtaining an enhanced video image; and the intelligent analysis and prediction unit is used for carrying out quantitative identification on the enhanced video image, obtaining pipeline defects in the video image and carrying out risk prediction. The problems that no available infrared monitoring equipment exists in a radiation area of an existing nuclear facility, the existing nuclear facility depends on an imported visible light camera (the problems of short service life, sensitivity to temperature, poor image quality and the like), and the existing nuclear facility lacks intelligent early warning capability are solved.

Sensing element transducers in a sensing system are connected to sensing element electronics by a switchable averaging network. The switchable averaging network may be configured to cause the sensing elements to operate in a sensing mode where the sensing elements all operate independently or in a calibration mode where the connected sensing elements have as an input a uniform signal generated by combining signals from all of the interconnected sensing element transducers. Signals output from the sensing system in the calibration mode may differ from the uniform signal due to unstable FPN (fixed-pattern noise) generated by the sensing element electronics and readout channels. These differences may be derived by comparing the signals output from the sensing system in the calibration mode to the uniform signal, and may be used to reduce FPN.

A method of an optical navigation device to be coupled to a host device includes: providing a pixel array circuit to capture and generate an image frame; performing a bandpass filter operation upon the image frame to remove a low-frequency image noise and a high-frequency image noise from the image frame so as to generate a bandpass-filtered image frame; and performing a correlation operation upon the bandpass-filtered image frame and a reference image frame to generate a displacement result between the bandpass-filtered image frame and the reference image frame as a motion result of the optical navigation device; the displacement result is to be reported to the host device if the displacement result indicates a motion.

This invention provides a fixed-pattern noise reduction method based on an encoder-decoder network, comprising: S1. Acquiring RAW images using an electronic imaging device equipped with a target image sensor, and creating a paired dataset for training a denoising model; S2. Performing necessary preprocessing on the dataset, expanding the dataset size and increasing its diversity through data augmentation; S3. Designing a lightweight encoder-decoder network, which consists of an encoder, connection layers, a decoder, and an output layer; S4. Training the encoder-decoder network based on the preprocessed paired dataset; S5. After the model training reaches convergence, loading the preprocessed, uncropped complete image into the model, and obtaining the denoised image through post-processing. This method utilizes the powerful fitting ability of the encoder-decoder network to eliminate prominent fixed-pattern noise in low-light images, and is applicable to different types of image sensors; the designed encoder-decoder network has low computational cost, making it suitable for resource-constrained edge devices.

The invention relates to an image sensor fixed pattern noise calibration system and method based on an FPGA, and the system comprises a parameter storage module which is used for storing calibrated row FPN calibration parameters and column FPN calibration parameters, the row FPN calibration parameters are stored according to the number of rows of an image sensor, and the column FPN calibration parameters are stored according to the number of columns of the image sensor; the column FPN calibration parameters are stored according to the number of columns of the image sensor. And the line calibration module is used for receiving the image data of the image sensor and carrying out calibration based on the line FPN calibration parameters to obtain line calibration result parameters. And the column calibration module is connected with the row calibration module, and is used for receiving the row calibration result parameter, performing calibration based on the row calibration result parameter and the column FPN calibration parameter, and obtaining the calibrated image data in the multi-slope HDR mode. The problem of how to effectively correct the multi-slope HDR mode fixed pattern noise under the constraint of limited storage resources in the prior art is solved.

The invention relates to an imaging system and a method of operating an image sensor. The imaging system may include an image sensor having an array of pixels arranged in rows and columns. A row driver circuit may be coupled to the pixel and may address a given row of the pixel based on a row address. Row randomization circuitry may be coupled to the row driver circuitry to dither the row address and thus randomize the order of reading out rows of a given column through column lines to sample and hold circuitry, the sample and hold circuitry including a plurality of capacitors for each column. The imaging system may include a multiplexer that de-randomizes the order of the row after passing through the sample and hold circuit. Alternatively or additionally, the order in which the signals from each column are stored using the plurality of capacitors may be randomized. In this manner, fixed pattern noise in the output image may be reduced or eliminated.

According to the circuit structure for the X-ray detector, the circuit structure is formed on the substrate by adopting the ink through a printing process. The circuit structure comprises a row driving circuit and a column acquisition circuit, wherein each of the row driving circuit and the column acquisition circuit comprises a gate line, a gate insulating layer, a semiconductor layer, a source line, a drain line and a protective layer. The gate insulating layer covers the gate line. The semiconductor layer covers the gate insulating layer. The source line and the drain line are arranged on the upper surface of the semiconductor layer. The protection layer covers the source line and the drain line. The circuit structure is formed by printing ink through a printing technology, in the X-ray imaging process, the circuit structure hardly generates absorptive'development ', fixed-mode noise such as image stripes and shadows caused by internal metal wiring is effectively avoided, and therefore the signal-to-noise ratio and uniformity of imaging are improved.

Dynamic systems and methods for fixed noise pattern calibrations and image corrections are provided. Imaging devices may be calibrated via the system by adjusting an imaging sensor exposure to acquire one or more black images. A global average pixel value is calculated to accumulate pixel values per column of the acquired image. The calculated global average pixel value is then saved as offset imaging data. An average pixel value per column of the imaging data based on the accumulated pixel values may also be calculated, and stored as offset imaging data. A correction matrix may be recomposed based on the offset imaging data and used for calibrating the imaging sensor, and for creating corrected images in or near real time.

A method includes of fixed pattern noise (FPN) reduction includes capturing, at runtime by an image sensor of an electronic device, noisy calibration video frames, and for each noisy calibration video frame: denoising, by a processor of the electronic device, the noisy calibration video frame to obtain a denoising residue frame, and determining, by the processor, whether the denoising residue frame is suitable for aggregation based on motion of the noisy calibration video frame relative to a previously captured noisy calibration video frame. The method further includes calibrating, by the processor, an FPN map for the image sensor based on an aggregation of the denoising residue frames that are determined to be suitable for aggregation, after the calibrating, capturing, by the image sensor, noisy target video frames, and generating, by the processor, clean target video frames from the noisy target video frames based on the calibrated FPN map.

Reduce the cost required to ensure the confidentiality of image data. [Solution] The image generation device 322 comprises a storage unit 318 and a noise reduction unit 321. The storage unit 318 stores fixed pattern noise 317 from the image sensor 308. The noise reduction unit 321 removes the fixed pattern noise 317 from the first image data 310 captured by the image sensor 308 to restore the second image data 324. With the image generation device 322, since the fixed pattern noise 317 is stored in the storage unit 318 in advance, the cost required to ensure the confidentiality of image data can be reduced.

The invention discloses an infrared thermal imaging array real-time optimization method based on an AI model, relates to the technical field of infrared imaging optimization, and is used for solving the problem that a real-time image optimization path is not clear. According to the method, a frame-level state vector and a region-level feature set are used as input, a region-level module activation mask is dynamically generated, exposure time, a dynamic range mapping curve and a confidence coefficient identifier are output through an AI model, parameter gating and backspacing are carried out under the constraints of a frame rate, delay and power consumption, and a region-level module activation mask is obtained. Non-uniformity correction, motion compensation space-time noise reduction and detail enhancement are selectively executed according to regions, a processing path and an image quality index are recorded, then non-interrupted self-supervised fine tuning is triggered under an approximate field-averaging condition, a fixed pattern noise template and related parameters are updated, and the image quality is improved. Therefore, key area priority and low-value area early exit are realized, redundancy calculation is reduced, infrared imaging contrast and dynamic range utilization rate are improved, and temperature measurement consistency and long-term stability in multiple scenes are enhanced.

A method of an optical navigation device to be coupled to a host device includes: providing a pixel array circuit to capture and generate an image frame; performing a bandpass filter operation upon the image frame to remove a low-frequency image noise and a high-frequency image noise from the image frame so as to generate a bandpass-filtered image frame; and performing a correlation operation upon the bandpass-filtered image frame and a reference image frame to generate a displacement result between the bandpass-filtered image frame and the reference image frame as a motion result of the optical navigation device; the displacement result is to be reported to the host device if the displacement result indicates a motion.

This application discloses a fixed-pattern noise correction method, device, and storage medium. The method includes: acquiring an image to be corrected; and acquiring a pre-calibrated noise response function and digital gain. The noise response function describes the mapping relationship between pixel values ​​and fixed-pattern noise. The method substitutes the pixel value of the current pixel in the image to be corrected into the noise response function to obtain the fixed-pattern noise corresponding to the current pixel. The fixed-pattern noise and digital gain are combined to obtain a final composite coefficient. Based on the composite coefficient, the pixel value of the current pixel is multiplied once to obtain the corrected value of the current pixel. By simultaneously performing fixed-pattern noise correction and digital gain correction within a single module using the composite coefficient, and directly rounding the product of the composite coefficient and the pixel value, the rounding error is linearly amplified with the digital gain to less than 1, avoiding image stripes under high digital gain and improving the image correction effect.

An imaging system may include an image sensor with an array of pixels arranged in rows and columns. Row driver circuitry may be coupled to the pixels and may address a given row of the pixels based on a row address. Row randomization circuitry may be coupled to the row driver circuitry to dither the row address and therefore randomize the order in which rows of a given column are read out over column lines to sample and hold circuitry that includes a plurality of capacitors for each column. The imaging system may include a multiplexer that de-randomizes the order of the rows after passing through the sample and hold circuitry. Alternatively or additionally, the order in which the plurality of capacitors is used to store the signals from each column may be randomized. In this way, fixed pattern noise in an output image may be reduced or eliminated.

The present application relates to the field of computational imaging, and particularly relates to a kind of cross bar anode single photon detector's computational imaging method, the computational imaging method is first by full field of view illumination screening effective data, the average output signal amplitude of each anode bar anode bar and the total average output signal amplitude of all anode bar are calculated to obtain correction factor;When target imaging, the original output signal of each anode bar is corrected using correction factor, then the effective signal data screening of the original output signal after correction is carried out, then the incident position coordinates are calculated by substituting effective signal data into Gaussian algorithm, then the incident position coordinates are mapped to mapping matrix and stretched to 256 gray scale display.The computational imaging method provided by the present application can suppress fixed pattern noise, improve imaging resolution and reduce image distortion.

A method includes of fixed pattern noise (FPN) reduction includes capturing, at runtime by an image sensor of an electronic apparatus, noisy calibration video frames, and for each noisy calibration video frame: denoising, by a processor of the electronic apparatus, the noisy calibration video frame to obtain a denoising residue frame, and determining, by the processor, whether the denoising residue frame is suitable for aggregation based on motion of the noisy calibration video frame relative to a previously captured noisy calibration video frame. The method further includes calibrating, by the processor, an FPN map for the image sensor based on an aggregation of the denoising residue frames that are determined to be suitable for aggregation, after the calibrating, capturing, by the image sensor, noisy target video frames, and generating, by the processor, clean target video frames from the noisy target video frames based on the calibrated FPN map.

The present application relates to the field of photoelectric sensing, and provides a detection panel, a detection apparatus, and an image processing method. The detection panel comprises: a plurality of pixels, each pixel comprising a photosensitive device and a thin film transistor. The plurality of pixels are arranged in an array to form a pixel array, the pixel array comprises a plurality of areas, and at least one target area comprises a first pixel and a second pixel. The thin film transistor in the first pixel is a first transistor; in a first direction, the overlap width between a gate of the first transistor and a first electrode of the first transistor is a first width, and the overlap width between the gate of the first transistor and a second electrode of the first transistor is a second width, the first width being greater than the second width; the thin film transistor in the second pixel is a second transistor; in a second direction, the overlap width between a gate of the second transistor and a first electrode of the second transistor is a third width, and the overlap width between the gate of the first transistor and the second electrode of the first transistor is a fourth width, the third width being smaller than the fourth width; and the first direction is opposite to the second direction. Fixed-pattern noise is reduced, and the imaging quality is improved.

An imaging system may include an image sensor with an array of pixels arranged in rows and columns. Row driver circuitry may be coupled to the pixels and may address a given row of the pixels based on a row address. Row randomization circuitry may be coupled to the row driver circuitry to dither the row address and therefore randomize the order in which rows of a given column are read out over column lines to sample and hold circuitry that includes a plurality of capacitors for each column. The imaging system may include a multiplexer that de-randomizes the order of the rows after passing through the sample and hold circuitry. Alternatively or additionally, the order in which the plurality of capacitors is used to store the signals from each column may be randomized. In this way, fixed pattern noise in an output image may be reduced or eliminated.

The invention provides a detection panel, a detection device and an image processing method, and relates to the field of photoelectric sensing. Each pixel comprises a photosensitive device and a thin film transistor; a plurality of pixel arrays are arranged to form a pixel array; the pixel array comprises a plurality of areas; the at least one target area comprises a first pixel and a second pixel; the thin film transistor in the first pixel is a first transistor; in the first direction, the overlapping width of the grid electrode of the first transistor and the first pole is a first width, and the overlapping width of the grid electrode of the first transistor and the second pole is a second width; the first width is greater than the second width; the thin film transistor in the second pixel is a second transistor; in the second direction, the overlapping width of the grid electrode of the second transistor and the first electrode is a third width, and the overlapping width of the grid electrode of the first transistor and the second electrode is a fourth width; the third width is smaller than the fourth width; the first direction is opposite to the second direction. Fixed mode noise is reduced, and imaging quality is improved.

Various techniques are provided to reduce fixed pattern noise (FPN) associated with the capturing of infrared images by infrared detectors operating in a dual band mode. In one example, a method includes operating a plurality of infrared detectors in a dual band mode to capture infrared images alternating between a first wavelength range and a second wavelength range. The operating comprises capturing a first infrared image corresponding to the first wavelength range, switching the infrared detectors to respond to the second wavelength range, and capturing a second infrared image corresponding to the second wavelength range. The method also includes calculating a correction term to compensate for dual band mode fixed pattern noise (FPN) in the second infrared image associated with the switching. The method also includes applying the correction term to the second infrared image to reduce the dual band mode FPN. Additional methods and systems are also provided.

This application relates to the field of image processing technology, specifically disclosing an infrared image processing method, apparatus, medium, and device. The method includes: performing photometric parameter separation processing on a current raw infrared image captured by an infrared camera to obtain an initial detail layer and an initial base layer at the current moment; performing denoising processing on the initial detail layer based on the target fixed-pattern noise at the current moment to obtain a target detail layer at the current moment; determining the target base layer at the current moment using an iterative optimization method based on the initial base layer from the previous moment, the maximum response value from the previous moment, the minimum response value from the previous moment, the initial maximum response value from the current moment, the initial minimum response value from the current moment, the initial base layer at the current moment, and a feature matching set; and performing image fusion processing based on the target detail layer and the target base layer to obtain a target infrared image. This application can improve the processing effect of infrared images.

The invention discloses an optical navigation device and a method thereof, and the method comprises the steps: providing a pixel array circuit, so as to capture and generate an image frame; performing band-pass filtering operation on the image frame by using an image band-pass filtering circuit to remove low-frequency image noise and high-frequency image noise in the image frame so as to generate an image frame after band-pass filtering; and performing correlation operation on the image frame after band-pass filtering and a reference image frame to generate a displacement result between the image frame after band-pass filtering and the reference image frame as a motion result of the optical navigation device, if the displacement result indicates motion, the displacement result is reported to the host device. According to the method, fixed pattern noise and time noise can be reduced, and quality reduction of correlation operation is avoided.

The invention relates to the technical field of image processing, and discloses a pixel signal reading circuit and method, an image sensor and electronic equipment, and the circuit comprises a pixel signal reading module, a switched capacitor amplifier, an analog-to-digital converter and a control module. A first signal node and a second signal node of the pixel signal reading module respectively store a pixel reset level and an illumination level; the switched capacitor amplifier adopts a single operational amplifier structure, and realizes self-return-to-zero sampling through a first feedback switch and a second feedback switch; the control module conducts the feedback switch in a sampling stage to capture operational amplifier imbalance, disconnects the feedback switch in an amplification stage and conducts the first signal node and the second signal node to enable the potentials to be equal, and differential signal amplification and column fixed mode noise compensation are achieved; the analog-to-digital converter quantizes the amplified signal. The functions of signal amplification, level shift and noise elimination are integrated through a single operational amplifier framework, and the circuit area and power consumption are remarkably reduced.

The application relates to a programmable gain amplifier circuit for extending the dynamic range of an image sensor, comprising a switched capacitor circuit and a negative feedback DC offset cancellation circuit; the switched capacitor circuit is used for twice correlated double sampling and amplification processing of the output signal of the image sensor pixel column, eliminating the fixed pattern noise and reset thermal noise, and outputting high-sensitivity and low-sensitivity analog voltages; the negative feedback DC offset cancellation circuit is used for reducing the influence of the offset voltage of the main operational amplifier on the output voltage by adopting an operational amplifier offset voltage storage mode. In the application, the image column fixed pattern noise caused by the offset voltage of the main operational amplifier can be greatly reduced through the operational amplifier offset storage technology, and the high-sensitivity and low-sensitivity analog signal inputs can be provided for the post-processing circuit in time through the twice correlated double sampling processing technology, so that the dynamic range of the image sensor is extended, and the image imaging quality is improved.

This invention proposes an image noise processing method, apparatus, image sensor, and storage medium. The method includes acquiring a reference column containing reference pixels with preset characteristics in a pixel array; determining the position of the reference column containing fixed-pattern noise from the reference column; and eliminating the fixed-pattern noise of valid pixels in the target column indicated by the position of the reference column in the pixel array. This invention enables noise elimination only for columns of pixels with fixed-pattern noise, avoiding impact on columns without fixed-pattern noise, thus improving noise reduction effectiveness and ensuring image rendering quality.