• Title/Summary/Keyword: Edge Preserving

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Background Subtraction for Moving Cameras based on trajectory-controlled segmentation and Label Inference

  • Yin, Xiaoqing;Wang, Bin;Li, Weili;Liu, Yu;Zhang, Maojun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.4092-4107
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    • 2015
  • We propose a background subtraction method for moving cameras based on trajectory classification, image segmentation and label inference. In the trajectory classification process, PCA-based outlier detection strategy is used to remove the outliers in the foreground trajectories. Combining optical flow trajectory with watershed algorithm, we propose a trajectory-controlled watershed segmentation algorithm which effectively improves the edge-preserving performance and prevents the over-smooth problem. Finally, label inference based on Markov Random field is conducted for labeling the unlabeled pixels. Experimental results on the motionseg database demonstrate the promising performance of the proposed approach compared with other competing methods.

The Characteristics of $\Delta$-shaped Filter for Full Screen Display on the FPD (FPD상에서 전화면 디스플레이를 위한 $\Delta$-형 필터의 특성)

  • 조화현;최철호;권병헌;최명렬
    • Journal of Korea Multimedia Society
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    • v.3 no.2
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    • pp.184-191
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    • 2000
  • In thid paper, we have analized the characteristics of $\Delta$-shaped filter based on preceeding study. The algorithm of $\Delta$-shaped filter for full screen display has been discussed including their edge-preserving characteristics and computaion complexity compared with the conventional algorithms. PSNR has been employed to compare the proposed method to the conventional algorithms. The proposed algorithm has been implemented using Synopsys VHDL tool. In addition, the features and trade off of the $\Delta$-shaped filter have been discussed.

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Total Ankle Arthroplasty in Ankle Arthritis with Coronal Plane Deformity (관상면 변형이 동반된 족관절염에서의 인공관절 치환술)

  • Yeo Kwon, Yoon;Kwang Hwan, Park;Jae Yong, Park
    • Journal of Korean Foot and Ankle Society
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    • v.26 no.4
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    • pp.157-162
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    • 2022
  • Total ankle arthroplasty has become a viable motion-preserving alternative to ankle arthrodesis, especially in the last two decades. Recent improvements have been achieved in the strength of implant design and surgical technique. Nevertheless, addressing preoperative deformities is essential for successful outcomes of total ankle arthroplasty. Residual malalignment can produce instability and edge loading, causing acceleration of polyethylene wear, followed by osteolysis and an increased risk of revision surgery. Therefore, the accompanying deformities and their correction techniques need to be comprehensively elucidated and understood. In this article, we provide a review of the application of total ankle arthroplasty in arthritis with coronal plane varus and valgus deformities.

PATN: Polarized Attention based Transformer Network for Multi-focus image fusion

  • Pan Wu;Zhen Hua;Jinjiang Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1234-1257
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    • 2023
  • In this paper, we propose a framework for multi-focus image fusion called PATN. In our approach, by aggregating deep features extracted based on the U-type Transformer mechanism and shallow features extracted using the PSA module, we make PATN feed both long-range image texture information and focus on local detail information of the image. Meanwhile, the edge-preserving information value of the fused image is enhanced using a dense residual block containing the Sobel gradient operator, and three loss functions are introduced to retain more source image texture information. PATN is compared with 17 more advanced MFIF methods on three datasets to verify the effectiveness and robustness of PATN.

Fast 3D Model Extraction Algorithm with an Enhanced PBIL of Preserving Depth Consistency (깊이 일관성을 보존하는 향상된 개체군기반 증가 학습을 이용한 고속 3차원 모델 추출 기법)

  • 이행석;장명호;한규필
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.1_2
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    • pp.59-66
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    • 2004
  • In this paper, a fast 3D model extraction algorithm with an enhanced PBIL of preserving depth consistency is proposed for the extraction of 3D depth information from 2D images. Evolutionary computation algorithms are efficient search methods based on natural selection and population genetics. 2D disparity maps acquired by conventional matching algorithms do not match well with the original image profile in disparity edge regions because of the loss of fine and precise information in the regions. Therefore, in order to decrease the imprecision of disparity values and increase the quality of matching, a compact genetic algorithm is adapted for matching environments, and the adaptive window, which is controlled by the complexity of neighbor disparities in an abrupt disparity point is used. As the result, the proposed algorithm showed more correct and precise disparities were obtained than those by conventional matching methods with relaxation scheme.

Hardware Design of Bilateral Filter Based on Window Division (윈도우 분할 기반 양방향 필터의 하드웨어 설계)

  • Hyun, Yongho;Park, Taegeun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.12
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    • pp.1844-1850
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    • 2016
  • The bilateral filter can reduce the noise while preserving details computing the filtering output at each pixels as the average of neighboring pixels. In this paper, we propose a real-time system based on window division. Overall performance is increased due to the parallel architectures which computes five rows in the kernel window simultaneously but with pipelined scheduling. We consider the tradeoff between the filter performance and the hardware cost and the bit allocation has been determined by PSNR analysis. The proposed architecture is designed with verilogHDL and synthesized using Dongbu Hitek 110nm standard cell library. The proposed architecture shows 416Mpixels/s (397fps) of throughput at 416MHz of operating frequency with 132K gates.

A Study of CNN-based Super-Resolution Method for Remote Sensing Image (원격 탐사 영상을 활용한 CNN 기반의 초해상화 기법 연구)

  • Choi, Yeonju;Kim, Minsik;Kim, Yongwoo;Han, Sanghyuck
    • Korean Journal of Remote Sensing
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    • v.36 no.3
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    • pp.449-460
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    • 2020
  • Super-resolution is a technique used to reconstruct an image with low-resolution into that of high-resolution. Recently, deep-learning based super resolution has become the mainstream, and applications of these methods are widely used in the remote sensing field. In this paper, we propose a super-resolution method based on the deep back-projection network model to improve the satellite image resolution by the factor of four. In the process, we customized the loss function with the edge loss to result in a more detailed feature of the boundary of each object and to improve the stability of the model training using generative adversarial network based on Wasserstein distance loss. Also, we have applied the detail preserving image down-scaling method to enhance the naturalness of the training output. Finally, by including the modified-residual learning with a panchromatic feature in the final step of the training process. Our proposed method is able to reconstruct fine features and high frequency information. Comparing the results of our method with that of the others, we propose that the super-resolution method improves the sharpness and the clarity of WorldView-3 and KOMPSAT-2 images.

Stereo Matching For Satellite Images using The Classified Terrain Information (지형식별정보를 이용한 입체위성영상매칭)

  • Bang, Soo-Nam;Cho, Bong-Whan
    • Journal of Korean Society for Geospatial Information Science
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    • v.4 no.1 s.6
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    • pp.93-102
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    • 1996
  • For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.

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Adaptive Unsharp Masking using Bilateral Filter (Bilateral Filter를 이용한 적응적 언샤프 마스킹)

  • Kim, Hak Gu;Lee, Dong Bok;Song, Byung Cheol
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.11
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    • pp.56-63
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    • 2012
  • In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.

An Edge Preserving Color Image Segmentation Using Mean Shift Algorithm and Region Merging Method (Mean Shift 알고리즘과 영역 병합 방법을 이용한 경계선 보존 컬러 영상 분할)

  • Kwak Nae-Joung;Kwon Dong-Jin;Kim Young-Gil
    • The Journal of the Korea Contents Association
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    • v.6 no.9
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    • pp.19-27
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    • 2006
  • Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

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