• Title/Summary/Keyword: peak signal-to-noise ratio (PSNR)

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Image Encryption using Complemented MLCA based on IBCA and 2D CAT (IBCA에 기초한 여원 MLCA와 2D CAT를 이용한 영상 암호화)

  • Nam, Tae-Hee;Kim, Seok-Tae;Cho, Sung-Jin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.4
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    • pp.34-41
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    • 2009
  • In this paper we propose a new image encryption method which utilizes Complemented MLCA(Complemented Maximum Length Cellular Automata) based on IBCA(Intermediate Boundary CA) and 2D CAT(Cellular Automata Transform). The encryption method is processed in the following order. First, Complemented MLCA is used to create a PN (pseudo noise) sequence, which matches the size of the original image. And, the original image goes through a XOR operation with the created sequence to convert the image into Complemented MLCA image. Then, the gateway value is set to produce a 2D CAT basis function. The produced basis function is multiplied by the encrypted MLCA image that has been converted to process the encipherment. Lastly, the stability analysis and PSNR(Peak Signal to Noise Ratio) verifies that the proposed method holds a high encryption quality status.

Constrained One-Bit Transform based Motion Estimation using Extension of Matching Error Criterion (정합 오차 기준을 확장한 제한된 1비트 변환 알고리즘 기반의 움직임 예측)

  • Lee, Sanggu;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.18 no.5
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    • pp.730-737
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    • 2013
  • In this paper, Constrained One-Bit Transform (C1BT) based motion estimation using extension of matching error criterion is proposed. C1BT based motion estimation algorithm exploiting Number of Non-Matching Points (NNMP) instead of Sum of Absolute Differences (SAD) that used in the Full Search Algorithm (FSA) facilitates hardware implementation and significantly reduces computational complexity. However, the accuracy of motion estimation is decreased. To improve inaccurate motion estimation, this algorithm based motion estimation extending matching error criterion of C1BT is proposed in this paper. Experimental results show that proposed algorithm has better performance compared with the conventional algorithm in terms of Peak-Signal-to-Noise-Ratio (PSNR).

Motion Picture Watermarking Algorithm (동영상 워터마킹 알고리즘)

  • 안일영;안용학
    • Convergence Security Journal
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    • v.2 no.1
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    • pp.35-47
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    • 2002
  • In this paper, we will provide an overview of the motion picture watermarking techniques. We will see previously proposed algorithms such as compressed domain watermarking, non-compressed domain watermarking and algorithms for realtime applications etc. We will see test results for signature embedding in motion picture. By spread spectrum method, we embed a signature in each frames. The quality of watermarked motion picture is measured by PSNR(peak signal to noise ratio) about several strengths of watermark. In watermark detection the sign of the correlation sum is the estimated embedded signature bits. We will see different mean PSNR with visual shape of the detected signature.

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Substitutability of Noise Reduction Algorithm based Conventional Thresholding Technique to U-Net Model for Pancreas Segmentation (이자 분할을 위한 노이즈 제거 알고리즘 기반 기존 임계값 기법 대비 U-Net 모델의 대체 가능성)

  • Sewon Lim;Youngjin Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.5
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    • pp.663-670
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    • 2023
  • In this study, we aimed to perform a comparative evaluation using quantitative factors between a region-growing based segmentation with noise reduction algorithms and a U-Net based segmentation. Initially, we applied median filter, median modified Wiener filter, and fast non-local means algorithm to computed tomography (CT) images, followed by region-growing based segmentation. Additionally, we trained a U-Net based segmentation model to perform segmentation. Subsequently, to compare and evaluate the segmentation performance of cases with noise reduction algorithms and cases with U-Net, we measured root mean square error (RMSE) and peak signal to noise ratio (PSNR), universal quality image index (UQI), and dice similarity coefficient (DSC). The results showed that using U-Net for segmentation yielded the most improved performance. The values of RMSE, PSNR, UQI, and DSC were measured as 0.063, 72.11, 0.841, and 0.982 respectively, which indicated improvements of 1.97, 1.09, 5.30, and 1.99 times compared to noisy images. In conclusion, U-Net proved to be effective in enhancing segmentation performance compared to noise reduction algorithms in CT images.

Robust and Reversible Image Watermarking Scheme Using Combined DCT-DWT-SVD Transforms

  • Bekkouch, Souad;Faraoun, Kamel Mohamed
    • Journal of Information Processing Systems
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    • v.11 no.3
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    • pp.406-420
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    • 2015
  • We present a secure and robust image watermarking scheme that uses combined reversible DWT-DCT-SVD transformations to increase integrity, authentication, and confidentiality. The proposed scheme uses two different kinds of watermarking images: a reversible watermark, $W_1$, which is used for verification (ensuring integrity and authentication aspects); and a second one, $W_2$, which is defined by a logo image that provides confidentiality. Our proposed scheme is shown to be robust, while its performances are evaluated with respect to the peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), normalized cross-correlation (NCC), and running time. The robustness of the scheme is also evaluated against different attacks, including a compression attack and Salt & Pepper attack.

Video Transmission Technique based on Deep Neural Networks for Optimizing Image Quality and Transmission Efficiency (영상 품질 및 전송효율 최적화를 위한 심층신경망 기반 영상전송기법)

  • Lee, Jong Man;Kim, Ki Hun;Park, Hyun;Choi, Jeung Won;Kim, Kyung Woo;Bae, Sung Ho
    • Journal of Broadcast Engineering
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    • v.25 no.4
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    • pp.609-619
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    • 2020
  • In accordance with a demand for high quality video streaming, it needs high data rate in limited bandwidth and more traffic congestion occurs. In particular, when providing real time video service, packet loss rate and bit error probability increase significantly. To solve these problems, a raptor code, which is one of FEC(Forward Error Correction) techniques, is pervasively used in the application layers as a method for improving real-time service quality. In this paper, we propose a method of determining image transmission parameters based on various deep neural networks to increase transmission efficiency at a similar level of image quality by using raptor codes. The proposed neural network uses the packet loss rate, video encoding rate and data rate as inputs, and outputs raptor FEC parameters and packet sizes. The results of the proposed method present that the throughput is 1.2% higher than that of the existing multimedia transmission technique by optimizing the transmission efficiency at a PSNR(Peak Signal-to-Noise Ratio) level similar to that of the existing technique.

The study of image quality evaluation and compression method using contourlet transform (정지 영상 화질 평가와 Contourlet 변환을 이용한 압축 방법에 관한 연구)

  • Jang, Jun-Ho;Kim, Young-Seop
    • Journal of the Semiconductor & Display Technology
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    • v.9 no.4
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    • pp.57-61
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    • 2010
  • The wavelet transform was adopted as the transform for JPEG2000. However, wavelet has weakness about smoothness along the contours and limited directional information. So we use to other transform, called contourlet transform in compression. Objective quality assessment methods currently used Peak signal to noise Ratio(PSNR). But that is not very well matched to perceived visual quality. So new image quality assessment is required. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. In addition we evaluated compression image quality using PSNR and SSIM. Finally contourlet transform has a good result about images with smooth contours and SSIM is good method for image evaluation compared to PSNR.

UHD TV Image Enhancement using Multi-frame Example-based Super-resolution (멀티프레임 예제기반 초해상도 영상복원을 이용한 UHD TV 영상 개선)

  • Jeong, Seokhwa;Yoon, Inhye;Paik, Joonki
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.3
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    • pp.154-161
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    • 2015
  • A novel multiframe super-resolution (SR) algorithm is presented to overcome the limitation of existing single-image SR algorithms using motion information from adjacent frames in a video. The proposed SR algorithm consists of three steps: i) definition of a local region using interframe motion vectors, ii) multiscale patch generation and adaptive selection of multiple optimum patches, and iii) combination of optimum patches for super-resolution. The proposed algorithm increases the accuracy of patch selection using motion information and multiscale patches. Experimental results show that the proposed algorithm performs better than existing patch-based SR algorithms in the sense of both subjective and objective measures including the peak signal-to-noise ratio (PSNR) and structural similarity measure (SSIM).

An Effective Noise Estimator for Use in Noise Reduction

  • Han, Hag-Yong;Kwon, Ho-Min;Lee, Sung-Mok;Lee, Gi-Dong;Kang, Bong-Soon
    • Journal of information and communication convergence engineering
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    • v.9 no.1
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    • pp.59-63
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    • 2011
  • Conventional noise reduction filtering schemes realize limited improvements of the peak signal-to-noise ratio (PSNR) in the low-level noisy images. The flatness degree and the edge information are effectively used to estimate the noise volume. We propose a noise estimator for reducing noise in the AWGN (additive white gaussian noise) corrupted images using three intermediate image maps (FGM(flatness gray map), FIM(flatness index map), NEM(noise estimate map)). The proposed noise estimator is fed into the conventional noise reduction filters as a pre-processor. The performance of noise reduction is tested in the various AWGN corrupted images.

Image Data Compression using Laplacian Pyramid Processing and Vector Quantization (Laplacian Pyramid Processing과 벡터 양자화 방법을 이용한 영상 데이터 압축)

  • 박광훈;안동순;차일환;윤대희
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.5
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    • pp.550-558
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    • 1988
  • This paper presents laplacian pyramid vector quantization (LPVQ) approach in which a vector quantizer is used to encode a series of quasi-bandpassed images generated by the laplacian pyramid processing. Performance of the LPVQ is compared to those of DCT domain methods at the same bit rate via computer simulations. Experimental results show that the PSNR's (peak signal-to-noise ratio) for the LPVQ are almost the same as those of the DCT based methods. However, subjective study indicates the LPVQ obtains slightly higher scores than the DCT based techniques.

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