• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.491-496
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• 2003

We present a new watermark design tool for digital images and digital videos that are based on human visual system (HVS) characteristics. In this tool, basic mechanisms (inhibitory and excitatory behaviour of cells) of HVS are used to determine image dependent upper bound values on watermark insertion. This allows us to insert maximai allowable transparent watermark, which in turn is extremely hard to attack with common image processing, Motion Picture Experts Group (MPEG) compression. As the number of details (e.g. edges) increases in an image, the HVS decrease its sensitivity to the details. In the same manner, as the number of motion increases in a video signal, the HVS decrease its sensitivity to the motions. We model this decreased sensitivity to the details and motions as an (motion) entropy masking. Entropy masking model can be efficiently used to increase the robustness of image and video watermarks. We have shown that our entropy-masking model provides watermark scheme with increased transparency and henceforth increased robustness.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.383-385
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• 2007

웨이블릿 화상 코딩 기법은 자연적으로 레이어드된 비트스트림을 생성해 내기 때문에, 주파수 제한적인 채널 상황에서 에러에 강한 성능을 나타내고 있다. 본 논문에서는 Progressive Image Coder의 성능을 비교하고 평가하는 새로운 기법인 시각적 엔트로피를 이용해, 웨이블릿 영역에서 시각적인 가중치를 이용해 정량화하려고 한다. 이 시각적인 가중치는 주파수 영역과 공간 영역에서, 인간의 시각 체계(HVS, human visual system)에 기반 하여 만들어진 것으로, 웨이블릿 계수들의 코딩 순서를 결정하는 기준으로 사용되고, 이렇게 해서 시각적인 화질을 개선할 수가 있다. 정규화된 채널 용량이 0.3일 때, 전송 이득은 시각적 엔트로피로 측정해 보았을 때 23% 이상 얻을 수 있다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.65-70
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• 2013

In this paper, we proposed color image watermarking using human visual system. A watermark is embedded by transforming a color image of RGB coordinate into a color image of HSI coordinate with considering that chromatic components are less sensitive than achromatic components. Watermark is embedded in the frequency domain of the chromatic channels by using discrete cosine transform. Watermark is extracted from watermarked image by using inverse discrete cosine transform. To verify the proposed method, a standard image and a fingerprint image are used for the original image and the watermark image, respectively. Simulation results are satisfied with invisibility and robustness from attacks as image compression.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1019-1022
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• 2002

The current paper proposes a wavelet-based digital watermarking algorithm using statistical characteristic of image and human visual system (HVS). The original image is decomposed into 4-level using a discrete wavelet transform (DWT), then the watermark is embedded into the perceptually significant coefficients (PSCs) of the image. In general, the baseband of a wavelet-decomposed image includes most of the energy of the original image, thereby having a crucial effect on the image quality. As such, to retain invisibility, the proposed algorithm does not utilize the baseband. Plus, the wavelet coefficients on the lowest level are also excluded in the watermark-embedding step, because these coefficients call be easily eliminated and modified by lossy compression and common signal processing. As such, the PSCs are selected from all subbands, except for the baseband and subbands on the lowest level. Finally, using the selected PSCs, the watermark is then embedded based on spatial masking of the wavelet coefficients so as to provide invisibility and robustness. Computer simulation results confirmed that the proposed watermarking algorithm was more invisible and robust than conventional algorithms.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.516-524
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• 2005

In this paper, a new watermarking scheme based on the POCS theory and human visual system is proposed. Using the POCS theory, watermarks are embedded into imperceptible image regions such as edge and strong texture area in the spatial domain. Also it is inserted into middle frequency band in the transform domain to achieve the robustness against compression and filtering, etc. In addition, different gain factors are employed into blocks classified by considering texture masking effect. By doing so, the proposed method has a novel property of having both the imperceptibility and the robustness simultaneously. Simulation results show that the proposed method has an excellent performance better than conventional approaches.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.369-382
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• 2018

We propose a single-shot high dynamic range (HDR) imaging algorithm using a deep convolutional neural network (CNN) for row-wise varying exposures in a single image. The proposed algorithm restores missing information resulting from under- and/or over-exposed pixels in an input image and reconstructs the raw radiance map. The main contribution of this work is the development of a loss function for the CNN employing the human visual system (HVS) properties. Then, the HDR image is obtained by applying a demosaicing algorithm. Experimental results demonstrate that the proposed algorithm provides higher-quality HDR images than conventional algorithms.

• The Journal of Natural Sciences
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• v.7
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• pp.67-73
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• 1995

In this paper, a new texture segmentation-based image coding technique which performs segmentation based on properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image into texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. It is very important to determine the proper block size for estimating the fractal dimension. Good quality reconstructed images are obtained with about 0.1 to 0.25 bit per pixel (bpp) for many different types of imagery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1469-1482
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• 1993

A new image coding technique has been proposed based on the wavelet transform. To achieve lower ceding rates and good qualities in reconstructed images, some of wavelet coefficients were removed by thresholding and quantized in accordance with the sensitivity of the human visual system(HVS). For each block of subimages in wavelet transform domain, block thresholding scheme has been used to remove the unimportant wavelet coefficients according to the frequency characteristic and statistical property of wavelet coefficients. The location information of quantized blocks and removed blocks were encoded using run-length coder which is effective for the exponential distribution. Quantized coefficients were encoded using variable length coder which matches well to their distribution. Simulation results show that the reconstructed images maintain high quality with the low bit rate, below 1.0 bits per pel.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.101-103
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• 2017

본 논문은 human visual system(HVS)에 따른 주파수 민감도와 공간에서 다양한 특성들을 구현하기 위한 신호처리 방법을 개발하였다. 인간의 눈은 주파수 성분에 따라 민감도가 다르며 초점에서 멀수록 인지 가능한 해상도가 떨어진다. 주파수 민감도를 구현하기 위해서 본 논문은 영상 신호의 에너지 스펙트럼 모양이 contrast sensitivity function(CSF)의 모양이 되도록 하여 영상 신호의 에너지를 증가시켰으며 신호 방향에 적응적인 multiband energy scaling 방법을 개발하였다. 기존의 시스템에서 능률만을 향상시키는 기존의 분석 모델과 비교하면 개발한 방법은 HVS에 좀 더 적절하고 선호되게 영상 신호를 처리할 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.68-75
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• 2006

In this paper, we propose an adaptive video watermarking method using human visual system(HVS) and characteristics of three-dimensional cosine transform (3D-DCT) cubes. We classify 3D-DCT cubes into three patterns according to the distribution of coefficients in the 3D-DCT cube: cube with motion and textures, cube with high textures and little motion, and cube with little textures and line motion. Images are also classified into three types according to the ratio of these patterns: images with motion and textures, images with high textures and little motion, and images with little textures and little motion. The proposed watermarking method adaptivelyinserts the watermark on the coefficients of the mid-range in the 3D-DCT cube using the appropriately learned sensitivity table and the proportional constants depending on the patterns of 3D-DCT cubes and types of images. Experimental results show that the proposed method achieves better performance in terms of invisibility and robustness than the previous method.