• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.17-26
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• 2012

This paper presents an image processing-based validation method for unrecognizable numbers in severely distorted license plate images which have been degraded by various factors including low-resolution, low light-level, geometric distortion, and periodic noise. Existing vehicle license plate recognition (LPR) methods assume that most of the image degradation factors have been removed before performing the recognition of printed numbers and letters. If this is not the case, conventional LPR becomes impossible. The proposed method adopts a novel approach where a set of reference number images are intentionally degraded using the same factors estimated from the input image. After a series of image processing steps, including geometric transformation, super-resolution, and filtering, a comparison using cross-correlation between the intentionally degraded reference and the input images can provide a successful identification of the visually unrecognizable numbers. The proposed method makes it possible to validate numbers in a license plate image taken under low light-level conditions. In the experiment, using an extended set of test images that are unrecognizable to human vision, the proposed method provides a successful recognition rate of over 95%, whereas most existing LPR methods fail due to the severe distortion.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.169-171
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• 2009

The histogram specification is to change the histogram shape of the image into the already defined shape. This technique can be applied usefully in various image processing fields which include a machine vision. However, the histogram specification technique has its basic limits. For example, the histogram does not have location information of pixel within the image and receives the digital image, which is stored through a quantization process, as an input. Namely, the accuracy of specification falls in the high-resolution image because the larger the resolution of image is becoming, the more the pixels having similar value are becoming. Therefore, we proposed the multiresolution histogram specification method for improving the accuracy of specification. Consequently, we can know that if the histogram specification is accomplished by using the proposed algorithm, destination image and source image were changed almost similarly.

• 디지털산업정보학회논문지
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• 제16권3호
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2000년도 춘계종합학술대회
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• pp.233-237
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• 2000

영상의 확대는 영상의 확장과 보간의 단계로 설명할 수 있다. 영상의 확대에 있어서 영상의 정보의 부족으로 인하여 실질적인 해상도의 향상이 이루어지지 않는다. 본 논문에서는 확대 영상의 실질적인 해상도 향상을 위하여 확대영상의 향상 기법에 대하여 연구하였다.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

• Imaging Science in Dentistry
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• 제50권4호
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• pp.331-337
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• 2020

Purpose: As cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images. Materials and Methods: Virtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images. Results: The images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1. Conclusion: VDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

• 방송공학회논문지
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• 제15권3호
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• pp.332-345
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• 2010

고선명 영상에 대한 수요가 증가하면서 다양한 방면에서 좀 더 선명하고 큰 영상을 보고 촬영하려는 요구가 늘어나고 있다. 특히 디스플레이 장치의 크기가 커지고 이에 따라 영상의 해상도가 커지면서 영상에서 나타나는 잡음이나 화질 저하가 이전에 비하여 더욱 더 눈에 띄게 나타나게 되었다. 본 논문에서 고선명 영상과 같이 해상도가 큰 영상의 색상과 명암 대비를 효과적이고 빠르게 개선하기 위한 방법을 제안한다. 고해상도 영상에서 처리 속도를 높이면서 효과적으로 화질 향상 방법을 적용하기 위해 고해상도 영상을 축소시킨 영상에서 화질 향상 방법에 필요한 변수를 추출해낸다. 영상의 색상을 향상시키기 위해 기존의 색채 항상성 방법을 개선시킨 방법을 적용하였고 명암 대비를 향상시키기 위해 경계 영역을 활용한 변형 히스토그램 평활화 방법을 적용하였다. 마지막으로 고해상도 영상을 촬영할 수 있는 디지털 캠코더를 이용하여 촬영한 실험 영상으로 제안하는 방법의 성능을 분석하였다.

• 대한전자공학회논문지SP
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• 제41권5호
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• pp.225-233
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• 2004

본 논문에서는 기존에 PC 모니터와 프린터 사이의 색 재현성 향상을 위해서 사용되던 색역폭 매핑 방법을 디스플레이 장치에 적용하기 위한 실시간 색역폭 매핑 방법을 제시하였다. 다양한 디스플레이 장치가 개발됨에 따라서 각 디스플레이 별로 색 재현성의 차이가 발생하고 있으며 기존의 색역폭 매핑 방법을 디지털 TV의 디스플레이 장치에 적용하기 위해서는 수 나노초 단위의 처리 속도가 필요하다. 이를 위하여 본 논문에서는 절감 3차원 룩업 테이블(three-dimensional reduced resolution look-up table)의 하드웨어 구조를 제안하고 이를 이용하여 색역폭 매핑을 실시간으로 수행하는 방법을 제공한다. 제안된 하드웨어 구조는 먼저 simulation을 통하여 타당성을 검증하였으며 이후 FPGA와 ASIC으로 구현되어 디지털 TV의 디스플레이 장치의 화질 개선에 성공적으로 적용되었다.

• 한국측량학회지
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• 제34권4호
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• pp.413-423
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• 2016

Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)-based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.

• 한국산학기술학회논문지
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• 제10권5호
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• pp.967-971
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• 2009

히스토그램 평활화 알고리즘은 영상의 화질개선을 위해서 사용되는 가장 필수적인 알고리즘이다. 이 알고리즘의 원형을 하드웨어로 구현하려면 제산기나 승산시가 반드시 필요하게 되는데, 영상의 해상도가 증가하거나 다양한 해상도에 적용할 경우에는 제산기나 승산기 구현에 수반되는 하드웨어 구현 비용이 대폭 증가한다는 문제점을 가지고 있다. 본 논문에서는 가산기와 감산기만으로 구현 가능한 히스토그램 평활화 알고리즘과 이에 대한 하드웨어 구조를 제안한다. 합성결과 제안한 하드웨어 구조는 일반적인 구현 방식 대비 UXGA 해상도에서 논리회로의 규모가 84.2% 감축된다.