A Hardware Method of Realizing IRFPA Nonuniformity Compressing Correction

Nonuniformity of Infrared Focal Plane Array (IRFPA) has greatly limited the quality of infrared imaging system, so nonuniformity must be corrected before using IRFPA. In order to reduce nonuniformity correction calculating amount and improve real-time nonuniformity correction speed, a new compressing correction method of utilizing hardware memory is presented. In this paper, memory compressing correction principle and implementing process are expounded in detail, and the hardware circuit diagram is given out. The experimental results prove that the method has simple circuit and excellent image quality and it easily realizes real-time nonuniformity correction.

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Research of IRFPA Non-uniformity Real-Time Correction Based on SOPC

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.474-476.277 ◽

2011 ◽

Vol 474-476 ◽

pp. 277-282

Author(s):

Bing Li ◽

Zheng Yu Yang ◽

Bao Ma

Keyword(s):

Real Time ◽

Infrared Imaging ◽

Imaging System ◽

Correction Method ◽

Focal Plane Arrays ◽

Bp Artificial Neural Network ◽

Infrared Imaging System ◽

Time Correction ◽

Simulation Results

<b>N</b>on-uniformity of infrared focal plane arrays (IRFPA) decreases the quality of the infrared imaging system greatly, so it is necessary to correct non-uniformity. Now the scene-based correction is being the focus of the study at home and abroad. Firstly, researching on normalized BP artificial neural network correction method in this paper, and then building a SOPC system on Altera's Stratix II EP2S60 DSP Development Board to realize the normalized BP real-time correction non-uniformity. The simulation results show that the SOPC system would meet the requirements of real-time correction. At the same time, the other method could be better to upgrade.

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The near infrared imaging system for the real-time protection of the JET ITER-like wall

Physica Scripta ◽

10.1088/1402-4896/aa8a14 ◽

2017 ◽

Vol T170 ◽

pp. 014027 ◽

Cited By ~ 6

Author(s):

A Huber ◽

D Kinna ◽

V Huber ◽

G Arnoux ◽

I Balboa ◽

...

Keyword(s):

Real Time ◽

Near Infrared ◽

Infrared Imaging ◽

Imaging System ◽

Near Infrared Imaging ◽

The Real ◽

Infrared Imaging System

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Real-time panoramic infrared imaging system based on FPGA

10.1117/12.867517 ◽

2010 ◽

Author(s):

Hao-Jun Zhang ◽

Yong-Ge Shen

Keyword(s):

Real Time ◽

Infrared Imaging ◽

Imaging System ◽

Infrared Imaging System

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A High-Performance Infrared Imaging System with Adaptive Contrast Enhancement

10.3233/faia210450 ◽

2021 ◽

Author(s):

Feng Deng ◽

Zhong Su ◽

Rui Wang ◽

Jun Liu ◽

Yanzhi Wang

Keyword(s):

Contrast Enhancement ◽

Real Time ◽

Infrared Imaging ◽

Imaging System ◽

Bilateral Filter ◽

Base Layer ◽

Low Contrast ◽

Infrared Imaging System ◽

Computing Performance ◽

Image Details

Most of the existing infrared imaging systems employ the scheme of FPGA/FPGA+DSP with numerous peripheral circuits, which leads to complex hardware architecture, limited system versatility, and low computing performance. It has become an intriguing technical problem worldwide to simplify the system structure while improving the imaging performance. In this paper, we present a novel real-time infrared imaging system based on the Rockchip’s RV1108 visual processing SoC (system on chip). Moreover, to address the problem of low contrast and dim details in infrared images with a high dynamic range, an adaptive contrast enhancement method based on bilateral filter is proposed and implemented on the system. First, the infrared image is divided into a base layer and a detail layer through bilateral filter, then the base layer is compressed by an adaptive bi-plateau histogram equalization algorithm, and finally a linear-weighted method is used to integrate the detail layer to obtain the image with enhanced details. The experimental results indicate that compared with traditional algorithms, our method can effectively improve the overall contrast of the image, while effectively retaining the image details without noise magnification. For an image of 320*240 pixels, the real-time processing rate of the system is 68 frames/s. The system has the characteristics of simplified structure, perceptive image details, and high computing performance.

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