• Title/Summary/Keyword: Adaptive Image Processing

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SAR Image De-noising Based on Residual Image Fusion and Sparse Representation

  • Ma, Xiaole;Hu, Shaohai;Yang, Dongsheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3620-3637
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    • 2019
  • Since the birth of Synthetic Aperture Radar (SAR), it has been widely used in the military field and so on. However, the existence of speckle noise makes a good deal inconvenience for the subsequent image processing. The continuous development of sparse representation (SR) opens a new field for the speckle suppressing of SAR image. Although the SR de-noising may be effective, the over-smooth phenomenon still has bad influence on the integrity of the image information. In this paper, one novel SAR image de-noising method based on residual image fusion and sparse representation is proposed. Firstly we can get the similar block groups by the non-local similar block matching method (NLS-BM). Then SR de-noising based on the adaptive K-means singular value decomposition (K-SVD) is adopted to obtain the initial de-noised image and residual image. The residual image is processed by Shearlet transform (ST), and the corresponding de-noising methods are applied on it. Finally, in ST domain the low-frequency and high-frequency components of the initial de-noised and residual image are fused respectively by relevant fusion rules. The final de-noised image can be recovered by inverse ST. Experimental results show the proposed method can not only suppress the speckle effectively, but also save more details and other useful information of the original SAR image, which could provide more authentic and credible records for the follow-up image processing.

An Adaptive Contrast Enhancement Method for Real-Time Processing (실시간 처리를 위한 적응형 콘트라스트 향상 기법)

  • Cho Hwa-Hyun;Choi Myung-Ryul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.1
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    • pp.51-57
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    • 2005
  • In this paper, we propose an adaptive contrast control method for the flat real-time processing. The proposed method has employed probability density function(PDF) in order to control a sudden change in image-brightness. In addition, the proposed algerian obtains the maximum contrast without affecting the processed image. In order to reduce hardware complexity, we have utilized approximated CDF based on sampling values. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of at: proposed method and the original ones.

Digital Image date Watermarking of Wavelet base (웨이브릿 기반의 디지털 영상 데이터 워터마킹)

  • Lee, Jeong-Ki;Kim, Kuk-Se;Park, Chan-Mo;Bae, Il-Ho;Lee, Joon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.11a
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    • pp.23-26
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    • 2003
  • 디지털로 신호를 표현하는 방법은 기존 아날로그 표현하는 방법에 비해 많은 장점을 가지고 있다. 하지만 디지털로 된 데이터는 언제 어디서든 대단위 복제가 가능하다. 즉, 저작권 침해, 불법 복제 및 배포, 손쉽게 위조할 수 있다는 점이 그것이다. 디지털 영상 정보의 보호를 위해 디지털 영상의 불법적인 내용 조작을 막고, 영상의 소유권을 보장할 수 있는 방법으로 디지털 워터마크(Digital Watermark)가 있다. 디지털 워터마크는 공개키 알고리즘이나 방화벽 등으로 해독된 영상에 대하여 부가적인 보호를 제공한다. 본 논문에서는 디지털 영상 데이터의 정보 보호를 위해 주파수 영역에서의 웨이브릿 변환(Wavelet Transform)을 이용한 이미지 적용 디지털 워터마킹(Image-Adaptive Digital Watermarking) 방법을 제안한다. 이미지 적용 웨이브릿(Image-Adaptive Wavelet)은 영상을 주파수적으로 분해하면서 각 대역들의 공간 영역에서의 정보를 함께 지니고 JND(Just noticeable difference)을 포함한다. 이미지 적응 웨이브릿의 이러한 특성을 이용하여 다해상도 분해하고, 손실 압축(Loss Compression)이나 필터링(Filtering), 잡음(Noise)등에 크게 영향받는 저주파 성분과 인간의 시각적으로 큰 의미를 갖는 고주파 성분의 특성을 이용하여 워터마크를 삽입한다.

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Implementation of Stereo Matching Algorithm using GPU (GPU를 이용한 스테레오 정합 알고리즘의 구현)

  • Choi, Hyun-Jun;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.3
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    • pp.583-588
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    • 2011
  • In this paper, we propose an adaptive variable-sized matching window method using the characteristic points of the image and a method to increase the reliability of the cross-consistency check to raise the correctness of the final disparity image. The proposed adaptive variable-sized window method segments the image with the color information, finds the characteristic points inside the window. Also the proposed algorithm implement using a graphic processing unit(GPU). The GPU, we used in this paper is GeForce GTX296 (NVIDIA) and we can use programming based on CUDA. The calculation speed realizes a speed approximately 128 times faster than that of a CPU.

A Statistically Model-Based Adaptive Technique to Unsupervised Segmentation of MR Images (자기공명영상의 비지도 분할을 위한 통계적 모델기반 적응적 방법)

  • Kim, Tae-Woo
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.1
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    • pp.286-295
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    • 2000
  • We present a novel statistically adaptive method using the Minimum Description Length(MDL) principle for unsupervised segmentation of magnetic resonance(MR) images. In the method, Markov random filed(MRF) modeling of tissue region accounts for random noise. Intensity measurements on the local region defined by a window are modeled by a finite Gaussian mixture, which accounts for image inhomogeneities. The segmentation algorithm is based on an iterative conditional modes(ICM) algorithm, approximately finds maximum ${\alpha}$ posteriori(MAP) estimation, and estimates model parameters on the local region. The size of the window for parameter estimation and segmentation is estimated from the image using the MDL principle. In the experiments, the technique well reflected image characteristic of the local region and showed better results than conventional methods in segmentation of MR images with inhomogeneities, especially.

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A Study of Resolving the Over Segmentation in Image using ATMF (ATMF를 이용한 영상의 과분할 방지에 관한 연구)

  • Park, Hyoung-Keun
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.735-740
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    • 2005
  • Video segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries, But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes that adaptive trimmed mean filter for resolving the over segmentation of image.

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A Study on Preprocessing Technique for Fingerprint Recognition using Applied Slit-Sum Method (Slit-Sum 방법을 응용한 지문인식 전처리 기술 연구)

  • 임철수;조성원
    • The Journal of the Korea Contents Association
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    • v.2 no.4
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    • pp.46-50
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    • 2002
  • This paper suggests the adaptive binary method which applies advanced silt sum technique, so that threshold value can be changed heuristically according to the brightness of captured fingerprint image. Through this research, we tried to resolve threshold value setting issue by the local differences of brightness of fingerprint image in the binary image preprocessing. The experimental results show that our proposed preprocessing method demonstrates the better recognition accuracy and can be applied to minutiae extraction algorithm for fingerprint recognition system.

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A Study On The Implementation of Real Time Image Composition System Using Adaptive Algorithm (적응 알고리즘을 이용한 실시간 영상합성 시스템 구현에 관한 연구)

  • Kim, Joong-Han;Choi, Doo-Il;Cho, Woo-Yeon
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.569-572
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    • 2002
  • In this study, a real-time image composition system was implemented using chroma key algorithm. To write a high Quality chroma key function based on processing of foreground and/or background frames before combining them into an output image, Adaptive 3-dimensional surface equation model was proposed. When the bright of room is changed or shadow of object is on the blue screen, proposed algorithm would still produce good result.

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Noise reduction algorithm for an image using nonparametric Bayesian method (비모수 베이지안 방법을 이용한 영상 잡음 제거 알고리즘)

  • Woo, Ho-young;Kim, Yeong-hwa
    • The Korean Journal of Applied Statistics
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    • v.31 no.5
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    • pp.555-572
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    • 2018
  • Noise reduction processes that reduce or eliminate noise (caused by a variety of reasons) in noise contaminated image is an important theme in image processing fields. Many studies are being conducted on noise removal processes due to the importance of distinguishing between noise added to a pure image and the unique characteristics of original images. Adaptive filter and sigma filter are typical noise reduction filters used to reduce or eliminate noise; however, their effectiveness is affected by accurate noise estimation. This study generates a distribution of noise contaminating image based on a Dirichlet normal mixture model and presents a Bayesian approach to distinguish the characteristics of an image against the noise. In particular, to distinguish the distribution of noise from the distribution of characteristics, we suggest algorithms to develop a Bayesian inference and remove noise included in an image.

A Adaptive Rendering Image Processing for Based on the Mobile (모바일을 기반으로 하는 적응적인 렌더링 영상 처리)

  • Ju, Heon-Sig;Kim, Ha-Jin
    • The KIPS Transactions:PartA
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    • v.10A no.5
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    • pp.425-432
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    • 2003
  • This paper presents an EMR(Electronic Medical Record) chart for efficient PDA through the quad tree image rendering based on the mobile. Using the intermediate image space algorithm instead of the final one for volume rendering, we have solved the probems of th eholes coming from the point-to-point to mapping. The quad-tree based on the delta-tree efficiently represents volume expressions and results in higher compression effects. With the volume rendering, we can decrease the rendering time and get a higher quality and efficiency for PDA through image based rendering.