scholarly journals Statistical Scene-Based Non-Uniformity Correction Method with Interframe Registration

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5395
Author(s):  
Baolin Lv ◽  
Shoufeng Tong ◽  
Qiaoyuan Liu ◽  
Haijiang Sun
Keyword(s):  
Statistical Method ◽  
Infrared Image ◽  
Gain Coefficient ◽  
Correction Method ◽  
Combination Method ◽  
Correction Coefficient ◽  
Initial Value ◽  
Registration Method ◽  
Pattern Noise ◽  
Fixed Pattern Noise

The non-uniform response in infrared focal plane array (IRFPA) detectors inevitably produces corrupted images with a fixed-pattern noise. In this paper, we present a novel and adaptive scene-based non-uniformity correction (NUC) method called Correction method with Statistical scene-based and Interframe Registration (CSIR), which realizes low delay calculation of correction coefficient for infrared image. This method combines the statistical method and registration method to achieve a better NUC performance. Specifically, CSIR estimates the gain coefficient with statistical method to give registration method an appropriate initial value. This combination method not only reduces the need of interactive pictures, which means lower time delay, but also achieves better performance compared to the statistical method and other single registration methods. To verify this, real non-uniformity infrared image sequences collected by ourselves were used, and the advantage of CSIR was compared thoroughly on frame number (corresponding to delay time) and accuracy. The results show that the proposed method could achieve a significantly fast and reliable fixed-pattern noise reduction with the effective gain and offset.

scholarly journals CMOS Fixed Pattern Noise Removal Based on Low Rank Sparse Variational Method

2020 ◽  
Vol 10 (11) ◽  
pp. 3694
Author(s):  
Tao Zhang ◽  
Xinyang Li ◽  
Jianfeng Li ◽  
Zhi Xu
Keyword(s):  
Variational Method ◽  
Noise Removal ◽  
Correction Method ◽  
Image Sensor ◽  
Low Rank ◽  
Statistical Characteristics ◽  
Parameter Adjustment ◽  
Structure Information ◽  
Pattern Noise ◽  
Fixed Pattern Noise

Fixed pattern noise (FPN) has always been an important factor affecting the imaging quality of CMOS image sensor (CIS). However, the current scene-based FPN removal methods mostly focus on the image itself, and seldom consider the structure information of the FPN, resulting in various undesirable noise removal effects. This paper presents a scene-based FPN correction method: the low rank sparse variational method (LRSUTV). It combines not only the continuity of the image itself, but also the structural and statistical characteristics of the stripes. At the same time, the low frequency information of the image is combined to achieve adaptive adjustment of some parameters, which simplifies the process of parameter adjustment, to a certain extent. With the help of adaptive parameter adjustment strategy, LRSUTV shows good performance under different intensity of stripe noise, and has high robustness.

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

Sensors ◽  
2015 ◽  
Vol 15 (9) ◽  
pp. 23496-23513 ◽  
Author(s):  
Zhenwang Liu ◽  
Jiangtao Xu ◽  
Xinlei Wang ◽  
Kaiming Nie ◽  
Weimin Jin
Keyword(s):  
Cmos Image Sensor ◽  
Correction Method ◽  
Image Sensor ◽  
Pattern Noise ◽  
Fixed Pattern Noise ◽  
Noise Correction

scholarly journals Simple Shading Correction Method for Brightfield Whole Slide Imaging

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3084
Author(s):  
Yoon-Oh Tak ◽  
Anjin Park ◽  
Janghoon Choi ◽  
Jonghyun Eom ◽  
Hyuk-Sang Kwon ◽  
...  
Keyword(s):  
State Of The Art ◽  
Correction Method ◽  
Input Image ◽  
Image Sequences ◽  
Whole Slide Imaging ◽  
Pattern Noise ◽  
Art Methods ◽  
Previous State ◽  
Fixed Pattern Noise

Whole slide imaging (WSI) refers to the process of creating a high-resolution digital image of a whole slide. Since digital images are typically produced by stitching image sequences acquired from different fields of view, the visual quality of the images can be degraded owing to shading distortion, which produces black plaid patterns on the images. A shading correction method for brightfield WSI is presented, which is simple but robust not only against typical image artifacts caused by specks of dust and bubbles, but also against fixed-pattern noise, or spatial variations in pixel values under uniform illumination. The proposed method comprises primarily of two steps. The first step constructs candidates of a shading distortion model from a stack of input image sequences. The second step selects the optimal model from the candidates. The proposed method was compared experimentally with two previous state-of-the-art methods, regularized energy minimization (CIDRE) and background and shading correction (BaSiC) and showed better correction scores, as smooth operations and constraints were not imposed when estimating the shading distortion. The correction scores, averaged over 40 image collections, were as follows: proposed method, 0.39 ± 0.099; CIDRE method, 0.67 ± 0.047; BaSiC method, 0.55 ± 0.038. Based on the quantitative evaluations, we can confirm that the proposed method can correct not only shading distortion, but also fixed-pattern noise, compared with the two previous state-of-the-art methods.

Registration method for infrared images under conditions of fixed-pattern noise

2012 ◽  
Vol 285 (9) ◽  
pp. 2293-2302 ◽  
Author(s):  
Chao Zuo ◽  
Qian Chen ◽  
Guohua Gu ◽  
Xiubao Sui
Keyword(s):  
Infrared Images ◽  
Registration Method ◽  
Pattern Noise ◽  
Fixed Pattern Noise

Suppression of fixed pattern noise for infrared image system

2008 ◽  
Author(s):  
Changhan Park ◽  
Jungsoo Han ◽  
Kyung-Hoon Bae
Keyword(s):  
Infrared Image ◽  
Image System ◽  
Pattern Noise ◽  
Fixed Pattern Noise

scholarly journals Averaging Pixel Current Adjustment Technique for Reducing Fixed Pattern Noise in the Bolometer-Type Uncooled Infrared Image Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1653
Author(s):  
Sang-Hwan Kim ◽  
Byoung-Soo Choi ◽  
Jimin Lee ◽  
Junwoo Lee ◽  
Jewon Lee ◽  
...  
Keyword(s):  
Dark Current ◽  
Small Deviation ◽  
Infrared Image ◽  
Image Sensor ◽  
Cmos Process ◽  
Readout Circuits ◽  
Active Pixel ◽  
Reference Pixel ◽  
Pattern Noise ◽  
Fixed Pattern Noise

In this paper, we propose an averaging pixel current adjustment technique for reducing fixed pattern noise (FPN) in the bolometer-type uncooled infrared image sensor. The averaging pixel current adjustment technique is composed of active pixel, reference pixel, and calibration circuit. Polysilicon resistors were used in each active pixel and reference pixel. Resistance deviation among active pixels integrated with the same resistance value cause FPN. The principle of the averaging pixel current adjustment technique for removing FPN is based on the subtraction of dark current of the active pixel from the dark current of the reference pixel. The subtracted current is converted into the voltage, which contains pixel calibration information. The calibration circuit is used to adjust the calibration current. After calibration, the nano-ampere current is output with small deviation. The proposed averaging pixel current adjustment technique is implemented by a chip composed of a pixel array, a calibration circuit, average current generators, and readout circuits. The chip was fabricated using a standard 0.35 μm CMOS process and its performance was evaluated.

scholarly journals Pixel Dark Current Calibration Method to Reduce Dark Fixed Pattern Noise in Amorphous Silicon Bolometer-type Uncooled Infrared Image Sensor

2020 ◽  
Vol 32 (10) ◽  
pp. 3261
Author(s):  
Sang-Hwan Kim ◽  
Jimin Lee ◽  
Hyeunwoo Kwen ◽  
Jae-Hyoun Park ◽  
Kyoung-Il Lee ◽  
...  
Keyword(s):  
Amorphous Silicon ◽  
Dark Current ◽  
Infrared Image ◽  
Calibration Method ◽  
Image Sensor ◽  
Pattern Noise ◽  
Fixed Pattern Noise
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