• Title/Summary/Keyword: Laplacian Image

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Vision based place recognition using Bayesian inference with feedback of image retrieval

  • Yi, Hu;Lee, Chang-Woo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.11a
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    • pp.19-22
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    • 2006
  • In this paper we present a vision based place recognition method which uses Bayesian method with feed back of image retrieval. Both Bayesian method and image retrieval method are based on interest features that are invariant to many image transformations. The interest features are detected using Harris-Laplacian detector and then descriptors are generated from the image patches centered at the features' position in the same manner of SIFT. The Bayesian method contains two stages: learning and recognition. The image retrieval result is fed back to the Bayesian recognition to achieve robust and confidence. The experimental results show the effectiveness of our method.

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A New Landsat Image Co-Registration and Outlier Removal Techniques

  • Kim, Jong-Hong;Heo, Joon;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.22 no.5
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    • pp.439-443
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    • 2006
  • Image co-registration is the process of overlaying two images of the same scene. One of which is a reference image, while the other (sensed image) is geometrically transformed to the one. Numerous methods were developed for the automated image co-registration and it is known as a timeconsuming and/or computation-intensive procedure. In order to improve efficiency and effectiveness of the co-registration of satellite imagery, this paper proposes a pre-qualified area matching, which is composed of feature extraction with Laplacian filter and area matching algorithm using correlation coefficient. Moreover, to improve the accuracy of co-registration, the outliers in the initial matching point should be removed. For this, two outlier detection techniques of studentized residual and modified RANSAC algorithm are used in this study. Three pairs of Landsat images were used for performance test, and the results were compared and evaluated in terms of robustness and efficiency.

A New Mapping Algorithm for Depth Perception in 3D Screen and Its Implementation (3차원 영상의 깊이 인식에 대한 매핑 알고리즘 구현)

  • Ham, Woon-Chul;Kim, Seung-Hwan
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.6
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    • pp.95-101
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    • 2008
  • In this paper, we present a new smoothing algorithm for variable depth mapping for real time stereoscopic image for 3D display. Proposed algorithm is based on the physical concept, called Laplacian equation and we also discuss the mapping of the depth from scene to displayed image. The approach to solve the problem in stereoscopic image which we adopt in this paper is similar to multi-region algorithm which was proposed by N.Holliman. The main difference thing in our algorithm compared with the N.Holliman's multi-region algorithm is that we use the Laplacian equation by considering the distance between viewer and object. We implement the real time stereoscopic image generation method for OpenGL on the circular polarized LCD screen to demonstrate its real functioning in the visual sensory system in human brain. Even though we make and use artificial objects by using OpenGL to simulate the proposed algorithm we assure that this technology may be applied to stereoscopic camera system not only for personal computer system but also for public broad cast system.

Application of Area Based Matching for the Automation of Interior Orientation (내부표정의 자동화를 위한 영역중심 영상정합기법 적용)

  • 유복모;염재홍;김원대
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.17 no.4
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    • pp.321-330
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    • 1999
  • Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

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A Performance Comparison Study of Lesion Detection Model according to Gastroscopy Image Quality (위 내시경 이미지 품질에 따른 병변 검출 모델의 성능 비교 연구)

  • Yul Hee Lee;Young Jae Kim;Kwang Gi Kim
    • Journal of Biomedical Engineering Research
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    • v.44 no.2
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    • pp.118-124
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    • 2023
  • Many recent studies have reported that the quality of input learning data was vital to the detection of regions of interest. However, due to a lack of research on the quality of learning data on lesion detetcting using gastroscopy, we aimed to quantify the impact of quality difference in endoscopic images to lesion detection models using Image Quality Assessment (IQA) algorithms. Through IQA methods such as BRISQUE (Blind/Referenceless Image Spatial Quality Evaluation), Laplacian Score, and PSNR (Peak Signal-To-Noise) algorithm on 430 sheets of high quality data (HQD) and 430 sheets of low quality data (PQD), we showed that there were significant differences between high and low quality images in lesion detecting through BRISQUE and Laplacian scores (p<0.05). The PSNR value showed 10.62±1.76 dB on average, illustrating the lower lesion detection performance of PQD than HQD. In addition, F1-Score of HQD showed higher detection performance at 77.42±3.36% while F1-Score of PQD showed 66.82±9.07%. Through this study, we hope to contribute to future gastroscopy lesion detection assistance systems that involve IQA algorithms by emphasizing the importance of using high quality data over lower quality data.

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.

An Approximation of Gaussian Pyramid Top Layer for Simplification of Image Pyramid-based Multi Scale Exposure Fusion Algorithm (이미지 피라미드 기반의 다중 노출 영상 융합기법 단순화를 위한 가우시안 피라미드 최상층 근사화)

  • Hwang, Tae Hun;Kim, Jin Heon
    • Journal of Korea Multimedia Society
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    • v.22 no.10
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    • pp.1160-1167
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    • 2019
  • Because of the dynamic range limitation of digital equipment, it is impossible to obtain dark and bright areas at the same time with one shot. In order to solve this problem, an exposure fusion technique for fusing a plurality of images photographed at different exposure amounts into one is being studied. Among them, Laplacian pyramid decomposition based fusion method can generate natural HDR image by fusing images of various scales. But this requires a lot of computation time. Therefore, in this paper, we propose an approximation technique that achieves similar performance and greatly shortens computation time. The concept of vanishing point image for approximation is introduced, and the validity of the proposed approach is verified by comparing the computation time with the resultant image.

Wavelet-Based Noise Estimation in Image (웨이브릿에 기반한 영상의 잡음추정)

  • 안태경;우동헌;김재호
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.747-750
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    • 2001
  • The paper presents an algorithm for estimating the variance of additive zero mean Gaussian noise in an image. The algorithm uses the wavelet transform which is a good tool for energy compaction. The algorithm consists of three steps. At first, high frequency components, wavelet coefficients in HH band, are generated from a noisy image by the wavelet transform. In a second step, high frequency components which are out of the noise range ate eliminated. Finally, if the image has many components eliminated in the previous step, then its noise estimated value is reduced. Experimental results show that the wavelet filter has better performance than the other high pass filters such as a Laplacian filter, residual from a median filter, residual from a mean filter, and a difference operator. In various images, the algorithm reduces 50% of estimated error on an average.

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

  • 원용관;김준식;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.5
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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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Consideration of Image Quality of Dithered Picture by Constrained Average Method Using Various Probability Distribution Models

  • Sato, Mitsuhiro;Hasegawa, Madoka;Kato, Shigeo
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1495-1498
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    • 2002
  • The constrained average method is one of dither methods which combines edge emphasis and grayscale rendition to provide legibility of textual region and proper quality of continuous tone region. How-ever, image quality of continuous tone region is insufficient compared to other dither methods, such as ordered dither methods or the error diffusion method. The constrained average method uses a uniform distribution function to decide number of lit pixels related to the average intensity in a picture area. However, actual distribution of continuous tone region is closer to the Laplacian distribution or triangle distribution. In this paper, we introduce various probability distributions and the actual luminance distribution to decide the threshold value of the constrained average method in order to improve image quality of dithered image.

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