scholarly journals Reference spectrum extraction and fixed-pattern noise removal in optical coherence tomography

2010 ◽  
Vol 18 (24) ◽  
pp. 24395 ◽  
Author(s):  
Sucbei Moon ◽  
Sang-Won Lee ◽  
Zhongping Chen
Keyword(s):  
Optical Coherence Tomography ◽  
Noise Removal ◽  
Reference Spectrum ◽  
Optical Coherence ◽  
Pattern Noise ◽  
Fixed Pattern Noise

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.

Iterative l_1-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging

2016 ◽  
Vol 33 (4) ◽  
pp. 630 ◽  
Author(s):  
Xuan Liu ◽  
Lijun Zhang ◽  
Mitchell Kirby ◽  
Richard Becker ◽  
Shaohai Qi ◽  
...  
Keyword(s):  
Fiber Bundle ◽  
Noise Removal ◽  
Endoscopic Imaging ◽  
Pattern Noise ◽  
Fixed Pattern Noise
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