Barrel Distortion

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Frantz Lohier - One of the best experts on this subject based on the ideXlab platform.

  • Real-time, color image Barrel Distortion removal
    2012 IEEE International Symposium on Circuits and Systems (ISCAS), 2012
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper describes a new hardware architecture for Barrel Distortion correction in a color video stream. Such Distortion is omnipresent in images acquired with a large field of view optics: wide-angle or fish-eye lenses. The designed platform is composed of a standard image sensor, a USB video class ASIC chip, a low cost FPGA and a SDRAM memory chip. Image processing algorithms are implemented in the FPGA, which is inserted between the sensor and the ASIC. The FPGA is connected to an external SDRAM in which a frame buffer is implemented. Barrel Distortion is modeled using a polynominal relationship between corrected and distorted image spaces. Combinatorial logic circuit at the frame buffer output validates correct ordering of luminance and chrominance bytes in the data stream. The proposed design is capable of removing geometric Distortion from 640 × 480 pixel images at the rate of 30 frames per second. Colors in reconstructed images are within ΔE = 2 from the originals in the CIELab color space.

  • ISCAS - Real-time, color image Barrel Distortion removal
    2012 IEEE International Symposium on Circuits and Systems, 2012
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper describes a new hardware architecture for Barrel Distortion correction in a color video stream. Such Distortion is omnipresent in images acquired with a large field of view optics: wide-angle or fish-eye lenses. The designed platform is composed of a standard image sensor, a USB video class ASIC chip, a low cost FPGA and a SDRAM memory chip. Image processing algorithms are implemented in the FPGA, which is inserted between the sensor and the ASIC. The FPGA is connected to an external SDRAM in which a frame buffer is implemented. Barrel Distortion is modeled using a polynominal relationship between corrected and distorted image spaces. Combinatorial logic circuit at the frame buffer output validates correct ordering of luminance and chrominance bytes in the data stream. The proposed design is capable of removing geometric Distortion from 640 × 480 pixel images at the rate of 30 frames per second. Colors in reconstructed images are within ΔE = 2 from the originals in the CIELab color space.

  • FPGA architecture for real-time Barrel Distortion correction of colour images
    2011 IEEE International Conference on Multimedia and Expo, 2011
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper presents a hardware architecture for real time Barrel Distortion correction of YUV 4∶2∶2 encoded color images. In our solution we are presenting an alternative implementation of the correction engine which is based on multiplications rather than trigonometric transforms. The system makes minimal use of resources thus being a good candidate for embedding into a single chip. Proposed solution is implemented in a cost-effective Spartan 3 Field Programmable Gate Array (FPGA). Our architecture is capable of processing QQVGA images at the rate of 30 frames per second (fps). Qualitative and quantitative examination confirm correct preservation of color information in processed images.

  • ICME - FPGA architecture for real-time Barrel Distortion correction of colour images
    2011 IEEE International Conference on Multimedia and Expo, 2011
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper presents a hardware architecture for real time Barrel Distortion correction of YUV 4∶2∶2 encoded color images. In our solution we are presenting an alternative implementation of the correction engine which is based on multiplications rather than trigonometric transforms. The system makes minimal use of resources thus being a good candidate for embedding into a single chip. Proposed solution is implemented in a cost-effective Spartan 3 Field Programmable Gate Array (FPGA). Our architecture is capable of processing QQVGA images at the rate of 30 frames per second (fps). Qualitative and quantitative examination confirm correct preservation of color information in processed images.

Henryk Blasinski - One of the best experts on this subject based on the ideXlab platform.

  • Real-time, color image Barrel Distortion removal
    2012 IEEE International Symposium on Circuits and Systems (ISCAS), 2012
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper describes a new hardware architecture for Barrel Distortion correction in a color video stream. Such Distortion is omnipresent in images acquired with a large field of view optics: wide-angle or fish-eye lenses. The designed platform is composed of a standard image sensor, a USB video class ASIC chip, a low cost FPGA and a SDRAM memory chip. Image processing algorithms are implemented in the FPGA, which is inserted between the sensor and the ASIC. The FPGA is connected to an external SDRAM in which a frame buffer is implemented. Barrel Distortion is modeled using a polynominal relationship between corrected and distorted image spaces. Combinatorial logic circuit at the frame buffer output validates correct ordering of luminance and chrominance bytes in the data stream. The proposed design is capable of removing geometric Distortion from 640 × 480 pixel images at the rate of 30 frames per second. Colors in reconstructed images are within ΔE = 2 from the originals in the CIELab color space.

  • ISCAS - Real-time, color image Barrel Distortion removal
    2012 IEEE International Symposium on Circuits and Systems, 2012
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper describes a new hardware architecture for Barrel Distortion correction in a color video stream. Such Distortion is omnipresent in images acquired with a large field of view optics: wide-angle or fish-eye lenses. The designed platform is composed of a standard image sensor, a USB video class ASIC chip, a low cost FPGA and a SDRAM memory chip. Image processing algorithms are implemented in the FPGA, which is inserted between the sensor and the ASIC. The FPGA is connected to an external SDRAM in which a frame buffer is implemented. Barrel Distortion is modeled using a polynominal relationship between corrected and distorted image spaces. Combinatorial logic circuit at the frame buffer output validates correct ordering of luminance and chrominance bytes in the data stream. The proposed design is capable of removing geometric Distortion from 640 × 480 pixel images at the rate of 30 frames per second. Colors in reconstructed images are within ΔE = 2 from the originals in the CIELab color space.

  • FPGA architecture for real-time Barrel Distortion correction of colour images
    2011 IEEE International Conference on Multimedia and Expo, 2011
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper presents a hardware architecture for real time Barrel Distortion correction of YUV 4∶2∶2 encoded color images. In our solution we are presenting an alternative implementation of the correction engine which is based on multiplications rather than trigonometric transforms. The system makes minimal use of resources thus being a good candidate for embedding into a single chip. Proposed solution is implemented in a cost-effective Spartan 3 Field Programmable Gate Array (FPGA). Our architecture is capable of processing QQVGA images at the rate of 30 frames per second (fps). Qualitative and quantitative examination confirm correct preservation of color information in processed images.

  • ICME - FPGA architecture for real-time Barrel Distortion correction of colour images
    2011 IEEE International Conference on Multimedia and Expo, 2011
    Co-Authors: Henryk Blasinski, Frantz Lohier
    Abstract:

    This paper presents a hardware architecture for real time Barrel Distortion correction of YUV 4∶2∶2 encoded color images. In our solution we are presenting an alternative implementation of the correction engine which is based on multiplications rather than trigonometric transforms. The system makes minimal use of resources thus being a good candidate for embedding into a single chip. Proposed solution is implemented in a cost-effective Spartan 3 Field Programmable Gate Array (FPGA). Our architecture is capable of processing QQVGA images at the rate of 30 frames per second (fps). Qualitative and quantitative examination confirm correct preservation of color information in processed images.

Joonki Paik - One of the best experts on this subject based on the ideXlab platform.

  • Correction of Barrel Distortion in Fisheye Lens Images Using Image-Based Estimation of Distortion Parameters
    IEEE Access, 2019
    Co-Authors: Joonki Paik
    Abstract:

    Images acquired by a fisheye lens camera contain geometric Distortion that results in deformation of the object's shape. To correct the lens Distortion, existing methods use prior information, such as calibration patterns or lens design specifications. However, the use of a calibration pattern works only when an input scene is a 2-D plane at a prespecified position. On the other hand, the lens design specifications can be understood only by optical experts. To solve these problems, we present a novel image-based algorithm that corrects the geometric Distortion. The proposed algorithm consists of three stages: i) feature detection, ii) Distortion parameter estimation, and iii) selection of the optimally corrected image out of multiple corrected candidates. The proposed method can automatically select the optimal amount of correction for a fisheye lens Distortion by analyzing characteristics of the distorted image using neither prespecified lens design parameters nor calibration patterns. Furthermore, our method performs not only on-line correction by using facial landmark points, but also off-line correction described in subsection III-C. As a result, the proposed method can be applied to a virtual reality (VR) or augmented reality (AR) camera with two fisheye lenses in a field-of-view (FOV) of 195°, autonomous vehicle vision systems, wide-area visual surveillance systems, and unmanned aerial vehicle (UAV) cameras.

  • Non-dyadic fisheye lens correction model for image enhancement
    Journal of The Optical Society of America A-optics Image Science and Vision, 2015
    Co-Authors: Jinho Park, Joonki Paik
    Abstract:

    This paper presents a non-dyadic framework to improve example-based enhancement of radially distorted images acquired by a very wide-angle lens. In order to remove both jagging and blurring artifacts in the correction process of the fisheye lens’ Barrel Distortion, the proposed method first performs non-dyadic or multiple-step geometric correction based on the parabolic equation-based lens Distortion model. At each correction step, an example-based image enhancement method removes undesired geometric correction artifacts such as jagging and blurring. Experimental results demonstrate that the proposed method outperforms existing fisheye lens image enhancement methods in the sense of both subjective and objective measures. Based on both theoretical advancement and experimental results, the proposed method can be used for various wide-view imaging applications including vehicle front- and rear-view cameras and wide-angle video surveillance systems.

  • ICCE - Fisheye lens-based surveillance camera for wide field-of-view monitoring
    2015 IEEE International Conference on Consumer Electronics (ICCE), 2015
    Co-Authors: Eunjung Chae, Gwanghyun Jo, Joonki Paik
    Abstract:

    This paper presents a single fisheye lens camera-based visual surveillance system for monitoring a wide area. A fisheye lens has a wider field-of-view (FOV) than normal lenses at the cost of a Barrel Distortion in the acquired image. After correcting the Barrel Distortion, the proposed algorithm detects objects, and performs tracking using a histogram-based Gaussian mixture model (GMM). Experimental results show that the proposed algorithm can efficiently detect objects by reducing the geometric Distortion of the input image. For this reason it is suitable for not only surveillance cameras but also consumer applications of video object detection and recognition.

  • Fisheye lens-based surveillance camera for wide field-of-view monitoring
    2015 IEEE International Conference on Consumer Electronics (ICCE), 2015
    Co-Authors: Eunjung Chae, Gwanghyun Jo, Joonki Paik
    Abstract:

    This paper presents a single fisheye lens camera-based visual surveillance system for monitoring a wide area. A fisheye lens has a wider field-of-view (FOV) than normal lenses at the cost of a Barrel Distortion in the acquired image. After correcting the Barrel Distortion, the proposed algorithm detects objects, and performs tracking using a histogram-based Gaussian mixture model (GMM). Experimental results show that the proposed algorithm can efficiently detect objects by reducing the geometric Distortion of the input image. For this reason it is suitable for not only surveillance cameras but also consumer applications of video object detection and recognition.

  • ICCAIS - Fisheye lens calibration using shifted lattice pattern and correction of Barrel Distortion using spatially adaptive interpolation
    The 2014 International Conference on Control Automation and Information Sciences (ICCAIS 2014), 2014
    Co-Authors: Eunjung Chae, Joonki Paik
    Abstract:

    In this paper, we present a novel fisheye lens calibration method and a spatially adaptive interpolation algorithm for correcting the radial Distortion of the lens. The proposed calibration method uses a shifted lattice pattern (SLP) image that contains sufficiently many feature points with different distances from the image center. The calibration is performed by matching all the points in the simulated image and the corresponding points in the input original image. After calibration, we correct the image using the proposed directionally adaptive interpolation to remove the peripheral degradation caused by the radial Distortion. The proposed method can accurately calibrate the fisheye lens and restore the radial Distortion without using complicated three-dimensional modeling. As a result, it can be applied to the various imaging systems using fisheye lens such as digital zooming, high resolution video surveillance, and vehicle rear view cameras.

V.k. Asari - One of the best experts on this subject based on the ideXlab platform.

  • A pipelined architecture for real-time correction of Barrel Distortion in wide-angle camera images
    IEEE Transactions on Circuits and Systems for Video Technology, 2005
    Co-Authors: V.k. Asari
    Abstract:

    An efficient pipelined architecture for the real-time correction of Barrel Distortion in wide-angle camera images is presented in this paper. The Distortion correction model is based on least-squares estimation to correct the nonlinear Distortion in images. The model parameters include the expanded/corrected image size, the back-mapping coefficients, Distortion center, and corrected center. The coordinate rotation digital computer (CORDIC) based hardware design is suitable for an input image size of 1028/spl times/1028 pixels and is pipelined to operate at a clock frequency of 40 MHz. The VLSI system will facilitate the use of a dedicated hardware that could be mounted along with the camera unit.

  • Non-linear spatial warping of endoscopic images: an architectural perspective for real time applications
    Microprocessors and Microsystems, 2002
    Co-Authors: V.k. Asari
    Abstract:

    Abstract Images captured with a typical endoscope show spatial Distortion, which necessitates spatial warping for subsequent analysis. In this paper, an efficient architecture for an embedded system for the real-time correction of Barrel Distortion in endoscopic images is proposed. The spatial warping procedure follows a methodology based on least-squares estimation to correct the non-linear Distortion in the endoscopic images. A mathematical model of polynomial mapping is used to map the images from distorted image space onto the warped image space. The model parameters include the expansion polynomial coefficients, Distortion centre, and corrected centre. The spatial warping model is applied to several gastrointestinal images. The spatial warping algorithm is mapped onto a linear array of simple processing elements with each element of a particular segment communicating with its nearest neighbours. Currently, a prototype of the VLSI architecture for an image of size 256×192 is being designed and built. The functional simulation results obtained in the warping architecture are encouraging. The VLSI based system will facilitate the use of a dedicated module that could be mounted along with the endoscopy unit.

Hong-yi Huang - One of the best experts on this subject based on the ideXlab platform.

  • Time Multiplexed VLSI Architecture for Real-Time Barrel Distortion Correction in Video-Endoscopic Images
    IEEE Transactions on Circuits and Systems for Video Technology, 2011
    Co-Authors: Shih-lun Chen, Hong-yi Huang
    Abstract:

    A low-cost very large scale integration (VLSI) implementation of real-time correction of Barrel Distortion for video-endoscopic images is presented in this paper. The correcting mathematical model is based on least-squares estimation. To decrease the computing complexity, we use an odd-order polynomial to approximate the back-mapping expansion polynomial. By algebraic transformation, the approximated polynomial becomes a monomial form which can be solved by Hornor's algorithm. With the iterative characteristic of Hornor's algorithm, the hardware cost and memory requirement can be conserved by time multiplexed design. In addition, a simplified architecture of the linear interpolation is used to reduce more computing resource and silicon area. The VLSI architecture of this paper contains 13.9-K gates by using a 0.18 μm CMOS process. Compared with some existing Distortion correction techniques, this paper reduces at least 69% hardware cost and 75% memory requirement.