• Title/Summary/Keyword: Image decomposition

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Accurate Segmentation Algorithm of Video Dynamic Background Image Based on Improved Wavelet Transform

  • Ming, Ming
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.711-718
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    • 2022
  • In this paper, an accurate segmentation algorithm of video dynamic background image (VDBI) based on improved wavelet transform is proposed. Based on the smooth processing of VDBI, the traditional wavelet transform process is improved, and the two-layer decomposition of dynamic image is realized by using two-dimensional wavelet transform. On the basis of decomposition results and information enhancement processing, image features are detected, feature points are extracted, and quantum ant colony algorithm is adopted to complete accurate segmentation of the image. The maximum SNR of the output results of the proposed algorithm can reach 73.67 dB, the maximum time of the segmentation process is only 7 seconds, the segmentation accuracy shows a trend of decreasing first and then increasing, and the global maximum value can reach 97%, indicating that the proposed algorithm effectively achieves the design expectation.

Fractal Image Compression Using QR Algorithm (QR 알고리즘을 이용한 프렉탈 영상압축)

  • Han, Kun-Hee;Kim, Tae-Ho;Jun, Byoung-Min
    • Journal of the Korean Society of Industry Convergence
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    • v.3 no.4
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    • pp.369-378
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    • 2000
  • Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

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An Watermarking Method Based on Singular Vector Decomposition and Vector Quantization Using Fuzzy C-Mean Clustering (특이치 분해와 Fuzzy C-Mean(FCM) 군집화를 이용한 벡터양자화에 기반한 워터마킹 방법)

  • Lee, Byung-Hee;Jang, Woo-Seok;Kang, Hwan-Il
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.964-969
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    • 2007
  • In this paper, we propose the image watermarking method for good compression ratio and satisfactory image quality of the cover image and the embedding image. This method is based on the singular value decomposition and the vector quantization using fuzzy c-mean clustering. Experimental results show that the embedding image has invisibility and robustness to various serious attacks. The advantage of this watermarking method is that we can achieve both the compression and the watermarking method for the copyright protection simultaneously.

Improvement of Image Sensor Performance through Implementation of JPEG2000 H/W for Optimal DWT Decomposition Level

  • Lee, Choel;Kim, BeomSu;Jeon, ByungKook
    • International journal of advanced smart convergence
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    • v.6 no.1
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    • pp.68-75
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    • 2017
  • In this paper, a particular application of digital photos, remote sensing, remote shooting air moving, high-resolution and high compression of medical images required by remote shooting of JPEG2000 standard applied in the field of hardware design, production was implemented. JPEG2000 standard for image compression using the software implementation of the processing speed is very slow compared to conventional JPEG disadvantages, and also the standard of JPEG2000 DWT (Discrete wavelet transform) to improve the level of compression for image data if processing speed is a phenomenon that has degraded. In order to solve these JPEG2000 compression / decompression groups were designed and applied. In this paper, the optimal JPEG2000 compression / reservoir hardware by changing the level for still image compression, faster computation speed and quality has shown improvement.

An Watermarking Method based on Singular Vector Decomposition and Vector Quantization using Fuzzy C-Mean Clustering (특이치 분해와 Fuzzy C-Mean(FCM) 클러스터링을 이용한 벡터양자화에 기반한 워터마킹 방법)

  • Lee, Byung-Hee;Kang, Hwan-Il;Jang, Woo-Seok
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10d
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    • pp.7-11
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    • 2007
  • In this paper the one of image hide method for good compression ratio and satisfactory image quality of the cover image and the embedding image based on the singular value decomposition and the vector quantization using fuzzy c-mean clustering is introduced. Experimental result shows that the embedding image has invisibility and robustness to various serious attacks.

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ILLUMINATION ADUSTMENT FOR BRIDGE COATING IMAGES USING BEMD-MORPHOLOGY APPROACH

  • Po-Han Chen;Ya-Ching Yang;Luh-Maan Chang
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.224-229
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    • 2009
  • Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

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An adaptive method of multi-scale edge detection for underwater image

  • Bo, Liu
    • Ocean Systems Engineering
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    • v.6 no.3
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    • pp.217-231
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    • 2016
  • This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

SAR Image Processing Using SVD-Pseudo Spectrum Technique (SAR에 적용된 SVD-Pseudo Spectrum 기술)

  • Kim, Binhee;Kong, Seung-Hyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.3
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    • pp.212-218
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    • 2013
  • This paper presents an SVD(Singular Value Decomposition)-Pseudo Spectrum method for SAR (Synthetic Aperture Radar) imaging. The purpose of this work is to improve resolution and target separability of SAR images. This paper proposes SVD-Pseudo Spectrum method whose advantages are noise robustness, reduction of sidelobes and high resolution of spectral estimation. SVD-Pseudo Spectrum method uses Hankel Matrix of signal components and SVD (Singular Value Decomposition) method. In this paper, it is demonstrated that the SVD-Pseudo Spectrum method shows better performance than the matched filtering method and the conventional super-resolution based multiple signal classification (MUSIC) method in SAR image processing. The targets to be separated are modeled, and this modeled data is used to demonstrate the performance of algorithms.

PDE-based Image Interpolators

  • Cha, Young-Joon;Kim, Seong-Jai
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.12C
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    • pp.1010-1019
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    • 2010
  • This article presents a PDE-based interpolation algorithm to effectively reproduce high resolution imagery. Conventional PDE-based interpolation methods can produce sharp edges without checkerboard effects; however, they are not interpolators but approximators and tend to weaken fine structures. In order to overcome the drawback, a texture enhancement method is suggested as a post-process of PDE-based interpolation methods. The new method rectifies the image by simply incorporating the bilinear interpolation of the weakened texture components and therefore makes the resulting algorithm an interpolator. It has been numerically verified that the new algorithm, called the PDE-based image interpolator (PII), restores sharp edges and enhances texture components satisfactorily. PII outperforms the PDE-based skeleton-texture decomposition (STD) approach. Various numerical examples are shown to verify the claim.

Video Sequence Matching Using Normalized Dominant Singular Values

  • Jeong, Kwang-Min;Lee, Joon-Jae
    • Journal of Korea Multimedia Society
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    • v.12 no.6
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    • pp.785-793
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    • 2009
  • This paper proposes a signature using dominant singular values for video sequence matching. By considering the input image as matrix A, a partition procedure is first performed to separate the matrix into non-overlapping sub-images of a fixed size. The SVD(Singular Value Decomposition) process decomposes matrix A into a singular value-singular vector factorization. As a result, singular values are obtained for each sub-image, then k dominant singular values which are sufficient to discriminate between different images and are robust to image size variation, are chosen and normalized as the signature for each block in an image frame for matching between the reference video clip and the query one. Experimental results show that the proposed video signature has a better performance than ordinal signature in ROC curve.

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