• Title/Summary/Keyword: noise visibility function

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Non-natural Image Steganography Based on Noise Visibility Function(NVF) (Noise Visibility Function(NVF)를 이용한 비자연 영상에서의 스테가노그래피)

  • 홍지희;권오진
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1807-1810
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    • 2003
  • Steganography based on Just Noticeable Difference(JND) has been used for natural images. However, it has been recognized to have defects for the non-natural images such as scanned text images, cartoons, etc. In this paper, an alternative method is proposed to improve this problem. A new scheme is designed specially for the non-natural images. Instead of JND, Noise Visibility Function(NVF) is used. NVF value and edge strength value of each pixel ate combined to decide the embedding data capacity and the visibility of data embedded images have been improved specially for the non-natural images.

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Adaptive Watermarking Using Successive Subband Quantization and Perceptual Model Based on Multiwavelet Transform Domain (멀티웨이브릿 변환 영역 기반의 연속 부대역 양자화 및 지각 모델을 이용한 적응 워터마킹)

  • 권기룡;이준재
    • Journal of Korea Multimedia Society
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    • v.6 no.7
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    • pp.1149-1158
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    • 2003
  • Content adaptive watermark embedding algorithm using a stochastic image model in the multiwavelet transform is proposed in this paper. A watermark is embedded into the perceptually significant coefficients (PSCs) of each subband using multiwavelet transform. The PSCs in high frequency subband are selected by SSQ, that is, by setting the thresholds as the one half of the largest coefficient in each subband. The perceptual model is applied with a stochastic approach based on noise visibility function (NVF) that has local image properties for watermark embedding. This model uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The watermark estimation use shape parameter and variance of subband region. it is derive content adaptive criteria according to edge and texture, and flat region. The experiment results of the proposed watermark embedding method based on multiwavelet transform techniques were found to be excellent invisibility and robustness.

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Blind Watermarking Using HVS and Wavelet Transform (HVS 모델과 웨이블릿 변환을 이용한 블라인드 워터마킹)

  • 주상현;이선화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.11C
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    • pp.1169-1176
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    • 2003
  • In this paper, we propose a blind watermarking that embeds watermarks into wavelet middle frequency subbands using human visual system. Wavelet middle frequency pairs(MFP) show similar distortion against general image processing attacks such as compression and filtering. So the quantization between MFPs is more robust than conventional methods that directly quantize DWT coefficients. We use a noise visibility function(NVF) to obtain a good visual quality This is able to preserve embedding positions after many attacks. Our experimental results show that the proposed scheme is robust to various image processing such as JPEG, while preserving good visual quality above 44㏈.

Spatially Adaptive CLS Based Image Restoration (CLS 기반 공간 적응적 영상복원)

  • 백준기;문준일;김상구
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.10
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    • pp.2541-2551
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    • 1996
  • Human visual systems are sensitive to noise on the flat intensity area. But it becomes less sensitive on the edge area. Recently, many types of spatially adaptive image restoration methods have been proposed, which employ the above mentioned huan visual characteristics. The present paper presents an adaptive image restoration method, which increases sharpness of the edge region, and smooths noise on the flat intensity area. For edge detection, the proposed method uses the visibility function based on the local variance on each pixel. And it adaptively changes the regularization parameter. More specifically, the image to be restored is divided into a number of steps from the flat area to the edge regio, and then restored by using the finite impulse response constrained least squares filter.

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Adaptive Watermark Detection using Stochastical Decision Rule Based on Image characteristics (영상특성에 기반한 통계적 판정법을 이용한 적응 워터마크 검출 알고리즘)

  • 황의창;김희정;김현천;김종진;권기룡
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.11a
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    • pp.104-107
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    • 2003
  • 본 논문에서는 웨이브릿 영역에서 HVS 및 NVF 함수를 사용하여 영상특성에 기반한 통계적 판정법을 이용한 적응 워터마크 검출 알고리즘을 판정법을 제안한다. 워터마크는 4레벨로 분해된 웨이브릿 영역에서 JND(just noticeable difference) 특성과 NVF(noise visibility function)를 이용한 통계적 특성을 기반으로 정상상태 가우시안 모델에 따라 지각적 동조 특성을 이용하여 적응적으로 삽입하고, Bayes 이론 및 Neyman-Pearson 정리를 이용한 통계적 판정법을 이용하여 워터마크를 추출함으로써 기존의 통계적 판정법 보다 정확하게 워터마크 존재 유무를 판정 할 수 있음을 확인하였다.

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Adaptive Image Watermarking Using a Stochastic Multiresolution Modeling

  • Kim, Hyun-Chun;Kwon, Ki-Ryong;Kim, Jong-Jin
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.172-175
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    • 2002
  • This paper presents perceptual model with a stochastic rnultiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the SSQ(successive subband quantization). The watermark embedding is based on the computation of a NVF(noise visibility function) that have local image properties. This method uses non-stationary Gaussian model stationary Generalized Gaussian model because watermark has noise properties. In order to determine the optimal NVF, we consider the watermark as noise. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model use the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark benchmark test.

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DR Image Enhancement Using Multiscale Non-Linear Gain Control For Laplacian Pyramid Transformation (라플라시안 피라미드에서의 다중스케일 비선형 이득 조절을 이용한 DR 영상 개선)

  • Shin, Dong-Kyu;Lee, Jin-Su;Kim, Sung-Hee;Park, In-Sung;Kim, Dong-Youn
    • Journal of Biomedical Engineering Research
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    • v.28 no.2
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    • pp.199-204
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    • 2007
  • In digital radiography, to improve the contrast of digital radiography image, the multi-scale nonlinear amplification algorithm based on unsharp masking is one of the major image enhancement algorithms. In this paper, we used the Laplacian pyramid to decompose a digital radiography(DR) image. In our simulation, the DR image was decomposed into seven layers and the coefficients of the each layer was amplified with nonlinear function. We also imported a noise containment algorithm to limit noise amplification. To enhance the contrast of image, we proposed a new adaptive non-linear gain amplification coefficients. As a result of having applied to some clinical data, a detail visibility was improved significantly without unacceptable noise boosting. Images that acquired with the proposed adaptive non-linear gain coefficients have shown superior quality to those that applied similar gain control method and expected to be accepted in the clinical applications.

EXTRACTION OF WATERMARKS BASED ON INDEPENDENT COMPONENT ANALYSIS

  • Thai, Hien-Duy;Zensho Nakao;Yen- Wei Chen
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.407-410
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    • 2003
  • We propose a new logo watermark scheme for digital images which embed a watermark by modifying middle-frequency sub-bands of wavelet transform. Independent component analysis (ICA) is introduced to authenticate and copyright protect multimedia products by extracting the watermark. To exploit the Human visual system (HVS) and the robustness, a perceptual model is applied with a stochastic approach based on noise visibility function (NVF) for adaptive watermarking algorithm. Experimental results demonstrated that the watermark is perfectly extracted by ICA technique with excellent invisibility, robust against various image and digital processing operators, and almost all compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal components analysis (PCA) based compression.

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Content Adaptive Watermarking Using a Stochastic Image Modeling Based on Wavelet Transform Domain (웨이브릿 변환 영역에서 스토케스틱 영상 모델을 이용한 내용기반 적응 워터마킹)

  • 김현천;강균호;권기룡;김종진
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.11b
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    • pp.283-286
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    • 2002
  • 본 논문에서는 보다 효과적이고 강인한 워터마크 은닉을 위한 방법으로 웨이브릿 변환 영역에서 영상의 통계적 특성에 기초한 비정상상태(non-stationary)에서와 정상상태(stationary) 일반화 가우스(generalized Gaussian: GG)모델을 이용한 적응 워터마크 은닉 기술을 제안한다. 워터마크는 고주파 영역에서 연속 부대역 양자화(successive subband quantization: SSQ)를 이용하여 다해상도 영상의 웨이브릿 계수 중에서 시각적 중요 계수(perceptual significant coefficients: PSC)를 선택하여 삽입한다. 워터마크 은닉을 위한 지각 모델은 NVF(noise visibility function)함수에 의해 계산된다. 이것은 비정상상태와 정상상태의 통계적 특성을 이용하고, 국부영상 특성을 가진다. 은닉모델은 다해상도내의 각 부대역별 분산과 형상계수(shape parameter)를 사용한다. Stirmark benchmark test에 근거하여 여러 가능한 왜곡에 대한 실험에서 강인성과 비가시성에서의 우수함을 확인하였고, 비정상상태의 경우와 정상상태의 경우를 비교하였다.

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Perceptual Data Hiding Model with Adaptive Watermark Strength (적응적 워터마크 삽입강도를 갖는 지각적 데이터 은닉 모델)

  • 조영웅;장봉주;김응수;문광석;권기룡
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.11b
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    • pp.287-290
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    • 2002
  • 본 논문에서는 디지털 컨텐츠 저작권 보호를 위해 강인성과 비가시성의 유지를 위한 보다 효과적인 방법으로 웨이브릿 변환에서 적응적 워터마크 삽입강도를 갖는 지각적 데이터 은닉 모델을 제안한다. 먼저 영상을 9/7 쌍직교 웨이브릿 필터를 사용해 4레벨로 다해상도 분해한다. 다음으로 연속부대역 양자화(successive subband quantization)를 통한 시각적 중요계수(perceptually significant coefficient: PSC)들을 선정하여 선택된 계수들에 대해서만 워터마크 정보를 삽입한다. 지각 모델은 정상상태의 일반화 가우시안 모델(generalized gaussian model)로 추정된 NVF(noise visibility function)로 에지와 텍스쳐영역 그리고 평탄영역에 따라 각각 적응적으로 삽입되게 한다. 이는 각 서브밴드 내의 분산과 형상계수(shape parameter)에 의해 결정된다. 적응적 워터마크의 삽입강도를 갖기 위해 에지와 텍스쳐영역의 삽입강도는 각 서브밴드의 주파수 감도(frequency sensitivity)로 결정되고, 평탄영역의 삽입강도는 영상의 국부적 특성에 근거한 통계적 가중치를 사용한다. 삽입되는 워터마크는 랜덤시퀀스로 N(0,1)이다. 여러 가지 공격에 대한 실험으로 제안한 방법의 비가시성과 강인성을 확인한다.

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