• 제목/요약/키워드: Image pyramid

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투영을 이용한 피라미드 영상 부호화 (Pyramid Image Coding Using Projection)

  • 원용관;김준식;박래홍
    • 전자공학회논문지B
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    • 제30B권5호
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    • pp.90-102
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    • 1993
  • In this paper, we propose a prgressive image transmission technique using hierarchical pyramid data structure which is constructed based on the projection data of an image. To construct hierarchical Gaussian pyramids, we first divide an image into 4$\times$4 subblocks and generate the projection data of each block along the horizontal, vertical, diagonal, and antidiagonal directions. Among images reconstructed by backprojecting the projection data along a single direction, the one giving the minimum distortion is selected. The Gaussian pyramid is recursively generated by the proposed algorithm and the proposed Gaussian images are shown to preserve edge information well. Also, based on the projection concept a new transmission scheme of the lowest Laplacian plane is presented. Computer simulation shows that the quantitative performance of the proposed pyramid coding technique using projection concept is similar to those of the conventional methods with transmission rate reduced by 0.1 ~ 0.2 bpp and its subjective performance is shown to be better due to the edge preserving property of a projection operation.

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Dual Attention Based Image Pyramid Network for Object Detection

  • Dong, Xiang;Li, Feng;Bai, Huihui;Zhao, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권12호
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    • pp.4439-4455
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    • 2021
  • Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

계층 간 특징 복원-예측 네트워크를 통한 피라미드 특징 압축 (Pyramid Feature Compression with Inter-Level Feature Restoration-Prediction Network)

  • 김민섭;심동규
    • 방송공학회논문지
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    • 제27권3호
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    • pp.283-294
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    • 2022
  • 딥 러닝 네트워크에서 사용되는 특징 맵은 일반적으로 영상보다 데이터가 크며 특징 맵을 전송하기 위해서는 영상의 압축률보다 더 높은 압축률이 요구된다. 본 논문은 딥러닝 기반의 영상처리에서 객체의 크기에 대한 강인성을 가지는 FPN 구조의 네트워크에서 사용되는 피라미드 특징 맵을 높은 압축률로 전송하기 위해 제안한 복원-예측 네트워크를 통해 전송된 일부 계층의 피라미드 특징 맵으로 전송하지 않은 계층의 피라미드 특징 맵을 예측하며, 압축으로 인한 손상을 복원하는 구조를 제안한다. 제안한 방법의 COCO 데이터셋 2017 Train images에 대한 객체 탐지의 성능은 rate-precision 그래프에서 VTM12.0을 통해 특징 맵을 압축한 결과 대비 BD-rate 31.25%의 성능향상을 보였고, PCA와 DeepCABAC을 통한 압축을 수행한 방법 대비 BD-rate 57.79%의 성능향상을 보였다.

라플라시안 피라미드에서의 다중스케일 비선형 이득 조절을 이용한 DR 영상 개선 (DR Image Enhancement Using Multiscale Non-Linear Gain Control For Laplacian Pyramid Transformation)

  • 신동규;이진수;김성희;박인성;김동윤
    • 대한의용생체공학회:의공학회지
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    • 제28권2호
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    • pp.199-204
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    • 2007
  • In digital radiography, to improve the contrast of digital radiography image, the multi-scale nonlinear amplification algorithm based on unsharp masking is one of the major image enhancement algorithms. In this paper, we used the Laplacian pyramid to decompose a digital radiography(DR) image. In our simulation, the DR image was decomposed into seven layers and the coefficients of the each layer was amplified with nonlinear function. We also imported a noise containment algorithm to limit noise amplification. To enhance the contrast of image, we proposed a new adaptive non-linear gain amplification coefficients. As a result of having applied to some clinical data, a detail visibility was improved significantly without unacceptable noise boosting. Images that acquired with the proposed adaptive non-linear gain coefficients have shown superior quality to those that applied similar gain control method and expected to be accepted in the clinical applications.

라플라시안 피라미드와 주성분 분석을 이용한 가시광과 적외선 영상 합성 (Visible and NIR Image Synthesis Using Laplacian Pyramid and Principal Component Analysis)

  • 손동민;권혁주;이성학
    • 센서학회지
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    • 제29권2호
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    • pp.133-140
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    • 2020
  • This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

Pyramid Edge Detection과 Line Fitting을 이용한 퓨리에 기반의 영상정합 (Fourier Based Image Registration Using Pyramid Edge Detection and Line Fitting)

  • 김기백;김종수;최종수
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.999-1000
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    • 2008
  • Image Registration is used many works in image processing widely. But It is difficult to find the accuracy informations such as translation, rotation, and scaling between images. This paper proposes an algorithm that Fourier based image registration using the pyramid edge detection and line fitting. It can be estimated the informations by each sub-pixels. The proposed algorithm can be used for image registrations which high efficiency is required such as GIS, or MRI, CT, image mosaicing, weather forecasting, etc.

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Mean difference pyramid 영상의 점진적 전송을 위한 블록 적응 비트 배정 (A Block Adaptive Bit Allocation for Progressive Transmission of Mean Difference Pyramid Image)

  • 김종훈;신재범;심영석
    • 전자공학회논문지B
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    • 제30B권4호
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    • pp.130-137
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    • 1993
  • In this paper, A progressive coding of mean difference pyramid by Hadamard transform of the difference between two successive pyramid levels has been studied. A block adaptive bit allocation method based on ac energy of each sub-block has been proposed, which efficiently reduces the final distortion in the progressive transmission of image parameters. In our scheme, the dc energy equals the sum of the quantization errors of the Hadamard transform coefficients at previous level. Therefore proposed allocation method includes the estimation of dc energy at each pyramid level. Computer simulation results show some improvements in terms of MSE and picture quality over the conventional fixed allocation scheme.

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피라미드를 이용한 곡선 추적에 관한 연구 (CURVE EXTRACTION USING PYRAMID)

  • 김소연;조동섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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    • pp.193-196
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    • 1991
  • A method of extracting global, trend curves from input image that may locally not even contain small fragments of those curves using a hierarchical pyramid data structure is suggested. The smoothed input image is subsampled into a pyramid of lower-resolution versions by recursive computation of Gaussian-weighted sums. Trend curves are extracted by finding control points from ridges in these blurred images, and interpolating B-splines for those points.

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영상 피라미드 기반 영상 모자이크를 위한 접합선 추출 (Seamline Detection for Image Mosaicking with Image Pyramid)

  • 유은진
    • 산업경영시스템학회지
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    • 제46권3호
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    • pp.268-274
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    • 2023
  • Image mosaicking is one of the basic and important technologies in the field of application using images. The key of image mosaicking is to extract seamlines from a joint image. The method proposed in this paper for image mosaicking is as follows. The feature points of the images to be joined are extracted and the joining form between the two images is identified. A reference position for detection the seamlines were selected according to the joint form, and an image pyramid was created for efficient image processing. The outlines of the image including buildings and roads are extracted from the overlapping area with low resolution, and the seamlines are determined by considering the components of the outlines. Based on this, the seamlines in the high-resolution image was re-searched and finally the seamline for image mosaicking was determined. In addition, in order to minimize color distortion of the image with the determined seamline, a method of improving the quality of the mosaic image by fine correction of the mosaic area was applied. It was confirmed that the quality of the seamline extraction results applying the method proposed was reasonable.