检索结果-内蒙古大学图书馆

Shot noise and fixed-pattern noise Effects on Digital Hologram Reconstruction

OPTICS AND LASERS IN ENGINEERING 2021年 139卷

作者： Cheremkhin, Pavel A. Evtikhiev, Nikolay N. Krasnov, Vitaly V. Rodin, Vladislav G. Starikov, Rostislav S. Natl Res Nucl Univ MEPhI Moscow Engn Phys Inst Kashirskoe Shosse 31 Moscow Russia

Digital holography allows registering and reconstructing information about 3D objects and 3D scenes. There are several limitations related to reconstructed image quality: speckle noise, twin images, zero order, light (shot noise) and dark temporal noise, camera fixed-pattern noise (spatial noise), dynamic range, and quantization noise. These restrictions determine the maximum possible signal-to-noise ratio (SNR) of digital holograms and reconstructed images. This work is concerned with studying the effect of a digital camera's main noise components on hologram reconstruction. Analytical equations for estimation of SNR of reconstructed amplitude image were obtained. They relate to a number of values: shot noise, dark temporal noise, fixed-pattern noise, camera's dynamic range, quantization noise, reference and object beam intensities, and the ratio between the object area and the entire reconstructed field. The resulting equation was tested experimentally using digital holograms of diffusely scattering objects. Characteristics of different types of CCD and CMOS cameras were used: digital single-lens reflex (DSLR), scientific, industrial, and video surveillance cameras. The effect of the camera noise on the phase image reconstruction was also estimated. The resulting equations make it possible to estimate the camera noise's effect on the reconstructed images before the experiments were conducted. As a result, the illumination value, exposure time, object size, and other experimental conditions can be pre-selected to reduce the noise in holograms used in metrological and infrared applications and optical encryption.

关键词： digital holography image capture signal-to-noise ratio fixed-pattern noise shot noise noise in imaging systems

来源：评论

学校读者我要写书评

暂无评论

Two-Dimensional Calibration for fixed-pattern noise Reduction of Thermal Images

Two-Dimensional Calibration for Fixed-Pattern Noise Reductio...

引用

IEEE International Symposium on Circuits and Systems (IEEE ISCAS)

作者： Chen, Nan Zhang, Jiqing Zhong, Shengyou Mao, Wenbiao Hu, Douming Yao, Libin Kunming Inst Phys Kunming Yunnan Peoples R China

ISBN: (纸本)9781728103976

A two-dimensional calibration technique is proposed to reduce fixed-pattern noise in infrared thermal images for extending dynamic range of sampling integration time. Traditional two-point calibration generates correction coefficients by irradiance of two reference temperatures, providing excellent spatial noise performance for the predetermined sampling integration time. To break the limitation of invariable integration time, two-dimensional calibration is proposed, which generates correction coefficients not only under irradiance of two temperatures, but also with two integration times. By exploring information from both temperature and integration, the new approach can reduce fixed-pattern noise for different sampling integration time, requiring same computation complexity and hardware consumption as conventional two-point calibration. In experiments with infrared camera, the proposed method suppresses fixed-pattern noise to a low level with same correction coefficients for sampling integration time changing from 0.4 ms to 1.6 ms. Compared to traditional calibration-based approaches, the presented scheme extends dynamic range of integration time by four times.

关键词： Thermal imaging fixed-pattern noise nonuniformity correction calibration dynamic range

来源：评论

学校读者我要写书评

暂无评论

A Convolution-Based Approach for fixed-pattern noise Removal in OCR

A Convolution-Based Approach for Fixed-Pattern Noise Removal...

引用

International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Mo, Jiawei Wang, Baohua Zhang, Zezhou Chen, Zhengze Huang, Zeyin Zhang, Jiale Ni, Xuanhui Shenzhen Univ Coll Math & Stat Shenzhen 518060 Peoples R China

ISBN: (纸本)9781538669877

There is some fixed-pattern noise in the OCR text image and the denosing is needed to improve the accuracy of recognition. In this paper, a convolution-based approach for the fixed-pattern noise removal in OCR is proposed. The approach identifies the location of text content pixels and removes noise pixels based on the convolution kernel. The experiment shows that the approach is an effective way to remove the underline and improve the accuracy of recognition. For its generality, the algorithm is also applicable of removing other type of fixed-pattern noise.

关键词： fixed-pattern noise denoising convolution

来源：评论

学校读者我要写书评

暂无评论

Joint Removal of Random and fixed-pattern noise Through Spatiotemporal Video Filtering

引用

IEEE TRANSACTIONS ON IMAGE PROCESSING 2014年第10期23卷 4282-4296页

作者： Maggioni, Matteo Sanchez-Monge, Enrique Foi, Alessandro Tampere Univ Technol Dept Signal Proc Tampere 33720 Finland Noiseless Imaging Oy Ltd Tampere 33100 Finland

We propose a framework for the denoising of videos jointly corrupted by spatially correlated (i.e., nonwhite) random noise and spatially correlated fixed-pattern noise. Our approach is based on motion-compensated 3D spatiotemporal volumes, i.e., a sequence of 2D square patches extracted along the motion trajectories of the noisy video. First, the spatial and temporal correlations within each volume are leveraged to sparsify the data in 3D spatiotemporal transform domain, and then the coefficients of the 3D volume spectrum are shrunk using an adaptive 3D threshold array. Such array depends on the particular motion trajectory of the volume, the individual power spectral densities of the random and fixed-pattern noise, and also the noise variances which are adaptively estimated in transform domain. Experimental results on both synthetically corrupted data and real infrared videos demonstrate a superior suppression of the random and fixed-pattern noise from both an objective and a subjective point of view.

关键词： Video denoising spatiotemporal filtering fixed-pattern noise power spectral density adaptive transforms thermal imaging

来源：评论

学校读者我要写书评

暂无评论

Empirical frequency domain model for fixed-pattern noise in infrared focal plane arrays

引用

INFRARED PHYSICS & TECHNOLOGY 2014年 67卷 413-426页

作者： Perez, Francisco Pezoa, Jorge E. Figueroa, Miguel Torres, Sergio N. Univ Concepcion Dept Elect Engn Concepcion Chile Univ Concepcion Ctr Opt & Photon Concepcion Chile

In this paper, a new empirical model for the spatial structure of the fixed-pattern noise (FPN) observed in infrared (IR) focal-plane arrays (FPA) is presented. The model was conceived after analyzing, in the spatial frequency domain, FPN calibration data from different IR cameras and technologies. The analysis showed that the spatial patterns of the FPN are retained in the phase spectrum, while the noise intensity is determined by the magnitude spectrum. Thus, unlike traditional representations, the proposed model abstracts the FPN structure using one matrix for its magnitude spectrum and another matrix for its phase spectrum. Three applications of the model are addressed here. First, an algorithm is provided for generating random samples of the FPN with the same spatial pattern of the actual FPN. Second, the model is used to assess the performance of non-uniformity correction (NUC) algorithms in the presence of spatially and uncorrelated FPN. Third, the model is used to improve the NUC capability of a method that requires, as a reference, a proper FPN sample. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Infrared focal plane arrays fixed-pattern noise Spatial non-uniformity noise Non-uniformity correction

来源：评论

学校读者我要写书评

暂无评论

Current Mode Image Sensor With Improved Linearity and fixed-pattern noise

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2014年第6期61卷 1666-1674页

作者： Wu, Xiaotie Liu, Xilin Zhang, Milin Van der Spiegel, Jan Univ Penn Dept Elect & Syst Engn ESE Philadelphia PA 19104 USA

Currentmode active pixel sensors convert light intensity into an analog output current. A current mode image sensor enables simple implementation of focal plane algebraic functions but suffers from poor linearity and large fixed-patten noise. This paper analyzes the causes of the non-linearity of a current-mode image sensor including a theoretical derivation and numerical simulation. Previously reported linearity improvement methods are reviewed, while an architecture of a current mode image sensor with a voltage feedback loop between pixel output and the current conveyor for linearity enhancement is proposed. An image sensor array of 100 x 200 current mode pixels is fabricated in a 0.5 mu m 2P3M standard CMOS processing technology. Experimental results illustrate a 45% improvement of the linearity of the proposed imager. fixed pattern noise is reduced by 57.6% for the maximum readout current, which can be further reduced by another 51.5% after gain calibration. A signal to noise ratio of 49.6 dB is achieved.

关键词： Current mode image sensor fixed-pattern noise linear response

来源：评论

学校读者我要写书评

暂无评论

Deep Unfolding for Iterative Stripe noise Removal

Deep Unfolding for Iterative Stripe Noise Removal

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / International Joint Conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Fayyaz, Zeshan Platnick, Daniel Fayyaz, Hannan Farsad, Nariman Ryerson Univ Toronto ON Canada York Univ N York ON Canada

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

The non-uniform photoelectric response of infrared imaging systems results in fixed-pattern stripe noise being superimposed on infrared images, which severely reduces image quality. As the applications of degraded infrared images are limited, it is crucial to effectively preserve original details. Existing image destriping methods struggle to concurrently remove all stripe noise artifacts, preserve image details and structures, and balance real-time performance. In this paper we propose a novel algorithm for destriping degraded images, which takes advantage of neighbouring column signal correlation to remove independent column stripe noise. This is achieved through an iterative deep unfolding algorithm where the estimated noise of one network iteration is used as input to the next iteration. This progression substantially reduces the search space of possible function approximations, allowing for efficient training on larger datasets. The proposed method allows for a more precise estimation of stripe noise to preserve scene details more accurately. Extensive experimental results demonstrate that the proposed model outperforms existing destriping methods on artificially corrupted images on both quantitative and qualitative assessments.

关键词： Image denoising fixed-pattern noise infrared image sensors deep unfolding neural networks image restoration

来源：评论

学校读者我要写书评

暂无评论

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

引用

SENSORS 2023年第4期23卷 2054-2054页

作者： Zhang, Di Sun, He Wang, Dejiang Liu, Jinghong Chen, Cheng Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

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.

关键词： atmospheric transmittance long wave infrared non-uniformity correction two-point correction fixed-pattern noise

来源：评论

学校读者我要写书评

暂无评论

AN ALGEBRAIC NONUNIFORMITY CORRECTION ALGORITHM FOR HEXAGONALLY-SAMPLED INFRARED IMAGES: A SIMULATION STUDY

AN ALGEBRAIC NONUNIFORMITY CORRECTION ALGORITHM FOR HEXAGONA...

引用

IEEE International Conference on Image Processing (ICIP)

作者： Sakoglu, Unal Univ Houston Clear Lake Comp Engn Houston TX 77058 USA

ISBN: (纸本)9781665441155

Infrared imagery, like almost any other two-dimensional (2-D) imagery, have been traditionally sampled and acquired using a rectangular grid. Algebraic fixed-pattern noise/nonuniformity correction (NUC) algorithms work on this traditional rectangular grid mitigating the most dominant, bias/offset portion of the nonuniformity. On the other hand, it is well-known that hexagonal sampling grid captures more information in sampled data/imagery when compared to traditional rectangular sampling, and a hexagonal addressing scheme for hexagonally-sampled imagery, namely array set addressing scheme, was recently developed. In this work, we derive the bilinear interpolation equations between two image frames for hexagonally-sampled infrared imagery with bias/offset nonuniformity under the 2-D global motion of the scene or the camera, and apply the 2-D algebraic NUC algorithm to hexagonally-sampled imagery. We present a simulation of mid-wave infrared imagery with hexagonally-sampled pixel array with bias nonuniformity under simulated global translational motion, and we test the efficiency of the NUC algorithm on the simulated infrared imagery and compare the performance of the hexagonally-sampled pixel array imagery NUC results to those of the traditional rectangularly-sampled pixel array imagery.

关键词： infrared imagery fixed-pattern noise nonuniformity correction hexagonal sampling

来源：评论

学校读者我要写书评

暂无评论

Higher Quality Images for a Visible-Light CMOS Sensor by Suppressing Spatial Row-Wise noise with an Output-Capacitor-Less, Internal Low-Dropout Regulator 52

Higher Quality Images for a Visible-Light CMOS Sensor by Sup...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Zadeh, Ali E. Univ Southern Calif USC Dept Elect & Comp Engn 3740 McClintock Ave Los Angeles CA 90089 USA

ISBN: (纸本)9781728133201

Image quality of visible-light CMOS sensors normally suffers from fixed-pattern noise. Spatial row-wise noise in an image particularly is caused by pixel array power supply coupling. Common noise injection from a fluctuating power supply during pixel readout causes horizontal stripe noise because all signals in a row are affected by the noise simultaneously. By integrating an output capacitor-less low-dropout (LDO) regulator on chip to directly supply a regulated power to the imager pixel array exclusively, it is possible to reduce fixed-pattern row-wise noise considerably so that the row-stripe noise becomes invisible entirely. The LDO circuit uses internal inherent pixel array parasitic capacitances along with an integrated capacitor multiplier circuit to eliminate the need for an off-chip capacitor and thus isolates the pixel array from the external board components such as bond-wire, pad, and board traces. The LDO was designed and fabricated in 0.13 mu m - 2P4M CMOS image sensor process and was implemented within a five-megapixel visible-light CMOS imager to prove the functionality and performance. Experimental data are included and shown that the row-wise noise is reduced by more than factor of five, making it negligible (and invisible) compare to the temporal pixel noise.

关键词： Low-noise CMOS Imager Output Capacitor-less Low-Dropout Regulator fixed-pattern noise

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：