• 제목/요약/키워드: national image

검색결과 10,158건 처리시간 0.036초

Double Random Phase Encryption using Orthogonal Encoding for Multiple-Image Transmission

  • Lee, In-Ho;Cho, Myungjin
    • Journal of the Optical Society of Korea
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    • 제18권3호
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    • pp.201-206
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    • 2014
  • In this paper we extend double random phase encryption (DRPE) using orthogonal encoding from single-image transmission to multiple-image transmission. The orthogonal encoding for multiple images employs a larger Hadamard matrix than that for a single image, which can improve security. We provide a scheme for DRPE with an orthogonal codec, and a method for orthogonal encoding/decoding for multiple-image transmission. Finally, simulation results verify that the DRPE using orthogonal encoding for multiple images is more secure than both the conventional DRPE and the DRPE using orthogonal encoding for a single image.

필터링과 선형보간을 이용한 색연필스케치영상 생성 (COLOR PENCIL SKETCH IMAGE GENERATION BASED ON FILTERING AND LINEAR INTERPOLATION)

  • 애릭 히티마나;권오봉
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2012년도 추계학술발표대회
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    • pp.623-625
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    • 2012
  • In this paper, we present a method to automatically generate a color pencil sketch image from a photo. First the image is converted into a sketch using a gradient estimation and then the color pencil sketch is produced by linear interpolation with original image and the sketched image. The experimental results show that the final image has a visual aspect of a color pencil sketch like image.

GRAYSCALE IMAGE COLORIZATION USING A CONVOLUTIONAL NEURAL NETWORK

  • JWA, MINJE;KANG, MYUNGJOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제25권2호
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    • pp.26-38
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    • 2021
  • Image coloration refers to adding plausible colors to a grayscale image or video. Image coloration has been used in many modern fields, including restoring old photographs, as well as reducing the time spent painting cartoons. In this paper, a method is proposed for colorizing grayscale images using a convolutional neural network. We propose an encoder-decoder model, adapting FusionNet to our purpose. A proper loss function is defined instead of the MSE loss function to suit the purpose of coloring. The proposed model was verified using the ImageNet dataset. We quantitatively compared several colorization models with ours, using the peak signal-to-noise ratio (PSNR) metric. In addition, to qualitatively evaluate the results, our model was applied to images in the test dataset and compared to images applied to various other models. Finally, we applied our model to a selection of old black and white photographs.

심층 전이 학습을 이용한 이미지 검색의 문화적 특성 분석 (Analysis of Cultural Context of Image Search with Deep Transfer Learning)

  • Kim, Hyeon-sik;Jeong, Jin-Woo
    • 한국정보통신학회논문지
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    • 제24권5호
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    • pp.674-677
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    • 2020
  • The cultural background of users utilizing image search engines has a significant impact on the satisfaction of the search results. Therefore, it is important to analyze and understand the cultural context of images for more accurate image search. In this paper, we investigate how the cultural context of images can affect the performance of image classification. To this end, we first collected various types of images (e.g,. food, temple, etc.) with various cultural contexts (e.g., Korea, Japan, etc.) from web search engines. Afterwards, a deep transfer learning approach using VGG19 and MobileNetV2 pre-trained with ImageNet was adopted to learn the cultural features of the collected images. Through various experiments we show the performance of image classification can be differently affected according to the cultural context of images.

Variational Bayesian inference for binary image restoration using Ising model

  • Jang, Moonsoo;Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • 제29권1호
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    • pp.27-40
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    • 2022
  • In this paper, the focus on the removal noise in the binary image based on the variational Bayesian method with the Ising model. The observation and the latent variable are the degraded image and the original image, respectively. The posterior distribution is built using the Markov random field and the Ising model. Estimating the posterior distribution is the same as reconstructing a degraded image. MCMC and variational Bayesian inference are two methods for estimating the posterior distribution. However, for the sake of computing efficiency, we adapt the variational technique. When the image is restored, the iterative method is used to solve the recursive problem. Since there are three model parameters in this paper, restoration is implemented using the VECM algorithm to find appropriate parameters in the current state. Finally, the restoration results are shown which have maximum peak signal-to-noise ratio (PSNR) and evidence lower bound (ELBO).

비밀자료 삽입용량을 증가시키기 위한 비밀 공유 기반의 이중 이미지 가역 정보은닉 기법 (Dual Image Reversible Data Hiding Scheme Based on Secret Sharing to Increase Secret Data Embedding Capacity)

  • 김평한;유관우
    • 한국멀티미디어학회논문지
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    • 제25권9호
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    • pp.1291-1306
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    • 2022
  • The dual image-based reversible data hiding scheme embeds secret data into two images to increase the embedding capacity of secret data. The dual image-based reversible data hiding scheme can transmit a lot of secret data. Therefore, various schemes have been proposed until recently. In 2021, Chen and Hong proposed a dual image-based reversible data hiding scheme that embeds a large amount of secret data using a reference matrix, secret data, and bit values. However, in this paper, more secret data can be embedded than Chen and Hong's scheme. To achieve this goal, the proposed scheme generates polynomials and shared values using secret sharing scheme, and embeds secret data using reference matrix and septenary number, and random value. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other dual image-based reversible data hiding schemes.

A Modified Steering Kernel Filter for AWGN Removal based on Kernel Similarity

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • 제20권3호
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    • pp.195-203
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    • 2022
  • Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

Single-Image Dehazing based on Scene Brightness for Perspective Preservation

  • Young-Su Chung;Nam-Ho Kim
    • Journal of information and communication convergence engineering
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    • 제22권1호
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    • pp.70-79
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    • 2024
  • Bad weather conditions such as haze lead to a significant lack of visibility in images, which can affect the functioning and reliability of image processing systems. Accordingly, various single-image dehazing (SID) methods have recently been proposed. Existing SID methods have introduced effective visibility improvement algorithms, but they do not reflect the image's perspective, and thus have limitations that distort the sky area and nearby objects. This study proposes a new SID method that reflects the sense of space by defining the correlation between image brightness and haze. The proposed method defines the haze intensity by calculating the airlight brightness deviation and sets the weight factor of the depth map by classifying images based on the defined haze intensity into images with a large sense of space, images with high intensity, and general images. Consequently, it emphasizes the contrast of nearby images where haze is present and naturally smooths the sky region to preserve the image's perspective.

PARALLAX ADJUSTMENT FOR REALISTIC 3D STEREO VIEWING OF A SINGLE REMOTE SENSING IMAGE

  • Kim, Hye-Jin;Choi, Jae-Wan;Chang, An-Jin;Yu, Ki-Yun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.452-455
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    • 2007
  • 3D stereoscopic viewing of large scale imagery, such as aerial photography and satellite images, needs different parallaxes relative to the display scale. For example, when a viewer sees a stereoscopic image of aerial photography, the optimal parallax of its zoom-in image should be smaller than that of its zoom-out. Therefore, relative parallax adjustment according to the display scale is required. Merely adjusting the spacing between stereo images is not appropriate because the depths of the whole image are either exaggerated or reduced entirely. This paper focuses on the improving stereoscopic viewing with a single remote sensing image and a digital surface model (DSM). We present the parallax adjustment technique to maximize the 3D realistic effect and the visual comfort. For remote sensing data, DSM height value can be regarded as disparity. There are two possible kinds of methods to adjust the relative parallax with a single image performance. One is the DSM compression technique: the other is an adjustment of the distance between the original image and its stereo-mate. In our approach, we carried out a test to evaluate the optimal distance between a single remote sensing image and its stereo-mate, relative to the viewing scale. Several synthetic stereo-mates according to certain viewing scale were created using a parallel projection model and their anaglyphs were estimated visually. The occlusion of the synthetic stereo-mate was restored by the inpainting method using the fields of experts (FoE) model. With the experiments using QuickBird imagery, we could obtain stereoscopic images with optimized parallax at varied display scales.

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Optimization of exposure parameters and relationship between subjective and technical image quality in cone-beam computed tomography

  • Park, Ha-Na;Min, Chang-Ki;Kim, Kyoung-A;Koh, Kwang-Joon
    • Imaging Science in Dentistry
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    • 제49권2호
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    • pp.139-151
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    • 2019
  • Purpose: This study was performed to investigate the effect of exposure parameters on image quality obtained using a cone-beam computed tomography (CBCT) scanner and the relationship between physical factors and clinical image quality depending on the diagnostic task. Materials and Methods: CBCT images of a SedentexCT IQ phantom and a real skull phantom were obtained under different combinations of tube voltage and tube current (Alphard 3030 CBCT scanner, 78-90 kVp and 2-8 mA). The images obtained using a SedentexCT IQ phantom were analyzed technically, and the physical factors of image noise, contrast resolution, spatial resolution, and metal artifacts were measured. The images obtained using a real skull phantom were evaluated for each diagnostic task by 6 oral and maxillofacial radiologists, and each setting was classified as acceptable or unacceptable based on those evaluations. A statistical analysis of the relationships of exposure parameters and physical factors with observer scores was conducted. Results: For periapical diagnosis and implant planning, the tube current of the acceptable images was significantly higher than that of the unacceptable images. Image noise, the contrast-to-noise ratio (CNR), the line pair chart on the Z axis, and modulation transfer function (MTF) values showed statistically significant differences between the acceptable and unacceptable image groups. The cut-off values obtained using receiver operating characteristic curves for CNR and MTF 10 were useful for determining acceptability. Conclusion: Tube current had a major influence on clinical image quality. CNR and MTF 10 were useful physical factors that showed significantly associations with clinical image quality.