• Title/Summary/Keyword: Image intensity

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Shadow Detection Based Intensity and Cross Entropy for Effective Analysis of Satellite Image (위성 영상의 효과적인 분석을 위한 밝기와 크로스 엔트로피 기반의 그림자 검출)

  • Park, Ki-hong
    • Journal of Advanced Navigation Technology
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    • v.20 no.4
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    • pp.380-385
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    • 2016
  • Shadows are common phenomena observed in natural scenes and often bring a major problem that is affected negatively in colour image analysis. It is important to detect the shadow areas and should be considered in the pre-processing of computer vision. In this paper, the method of shadow detection is proposed using cross entropy and intensity image, and is performed in single image based on the satellite images. After converting the color image to a gray level image, the shadow candidate region has been estimated the optimal threshold value by cross entropy, and then the final shadow region has been detected using intensity image. For the validity of the proposed method, the satellite images is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow detection is well performed.

A High Image Compression for Computer Storage and Communication

  • Jang, Jong-Whan
    • The Journal of Natural Sciences
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    • v.4
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    • pp.191-220
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    • 1991
  • A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

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Single-Image Dehazing based on Scene Brightness for Perspective Preservation

  • Young-Su Chung;Nam-Ho Kim
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.70-79
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    • 2024
  • Bad weather conditions such as haze lead to a significant lack of visibility in images, which can affect the functioning and reliability of image processing systems. Accordingly, various single-image dehazing (SID) methods have recently been proposed. Existing SID methods have introduced effective visibility improvement algorithms, but they do not reflect the image's perspective, and thus have limitations that distort the sky area and nearby objects. This study proposes a new SID method that reflects the sense of space by defining the correlation between image brightness and haze. The proposed method defines the haze intensity by calculating the airlight brightness deviation and sets the weight factor of the depth map by classifying images based on the defined haze intensity into images with a large sense of space, images with high intensity, and general images. Consequently, it emphasizes the contrast of nearby images where haze is present and naturally smooths the sky region to preserve the image's perspective.

The Optimal Condition for Velocity Modulation

  • Park, Joon-Suk;Kim, Do-Nyun
    • 한국정보디스플레이학회:학술대회논문집
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    • 2003.07a
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    • pp.1157-1159
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    • 2003
  • The effect of the scan velocity modulation is studied. The effect of the velocity modulation on the picture image is judged from the intensity profile of the image. The intensity profile is obtained as time integral of moving Gaussian beam. To confirm the applicability of this integral formula, the measurement and simulation data is compared. And by calculating the intensity profile for different amounts of velocity modulation, the optimum modulation displacement that gives the best image quality is obtained. This optimum modulation displacement can be used in designing scan velocity modulation system.

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A Background Initialization for Video Surveillance

  • Lim Kang Mo;Lee Se Yeun;Shin Chang Hoon;Kim Yoon Ho;Lee Joo Shin
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.810-813
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    • 2004
  • In this paper, a background initialization for video surveillance proposed. The proposed algorithm is that the background images are sampled n frames during ${\Delta}t$ All Sampling frames are divided by $M{\times}N$ size block every frame. Average values of pixels for same location block of the sampling frames during ${\Delta}t$t are taken. then the maximum intensity $\alpha$ and the minimun intensity $\beta$ is obtained, respecticely. The intial by $M{\times}N$ size block, then average intensity $\eta$ of pixels for the block is obtained. If the average intensity $\eta$ is out of the initial range of the background image, it is decided the moving object image, and if the average intensity $\eta$ is included in the initial range of the background image. it is decided the background image. To examine the propriety of the proposed algorithm in this paper, the accuracy and robustness evaluation results for human and car in the indoor and outdoor enviroment. the error rate of the proposed method is less than the existing methods and the extraction rate of the proposed method is better than the existing methods.

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The effects of video quality by LED background image in the broadcasting lighting (방송조명에서 LED 배경화면이 영상품질에 미치는 영향 분석)

  • Kim, Yong-Kyu;Kim, Kyung-Ho;Lee, Seon-Hee;Choi, Seong-Jhin
    • Journal of Broadcast Engineering
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    • v.15 no.1
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    • pp.76-88
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    • 2010
  • Recently, LED background image devices are used for the production of broadcasting programs. But the effective advantages of LED background image devices are not realized for good HD video quality because the correlations between lighting sources and LED background image devices are not analyzed yet. In this paper, we analyze the color change and light intensity that lighting sources and the light intensity ratio of LED background images influence on a subject, making use of equipments used in real broadcasting, and examine the correlations between HD video quality and the light intensity ratio of LED background images. As a result in this experiment, the video is most expressed having an 20[IRE] effect on a subject when the light intensity of LED background image is 6%. When the LED background image is light, the light and darkness of video is distorted and when the LED background image is dark, the colors of image are distorted.

Adaptive Iterative Depeckling of SAR Imagery (반복 적응법에 의한 SAR 잡음 제거)

  • Lee, Sang-Hoon
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.126-129
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    • 2007
  • In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel type s as states of molecules in a lattice-like physical system defined on a GRF. Because of the MRFGRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular mteractions. The proposed adaptive iterative method was evaluated using simulation data generated by the Monte Carlo method. In the extensive experiments of this study, the proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

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SAR Despeckling with Boundary Correction

  • Lee, Sang-Hoon
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.270-273
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    • 2007
  • In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

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Adaptive Iterative Depeckling of SAR Imagery

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.455-464
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    • 2007
  • Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

Generating a True Color Image with Data from Scanning White-Light Interferometry by Using a Fourier Transform

  • Kim, Jin-Yong;Kim, Seungjae;Kim, Min-Gyu;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.3 no.5
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    • pp.408-414
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    • 2019
  • In this paper we propose a method to generate a true color image in scanning white-light interferometry (SWLI). Previously, a true color image was obtained by using a color camera, or an RGB multichannel light source. Here we focused on acquiring a true color image without any hardware changes in basic SWLI, in which a monochrome camera is utilized. A Fourier transform method was used to obtain the spectral intensity distributions of the light reflected from the sample. RGB filtering was applied to the intensity distributions, to determine RGB values from the spectral intensity. Through color corrections, a true color image was generated from the RGB values. The image generated by the proposed method was verified on the basis of the RGB distance and peak signal-to-noise ratio analysis for its effectiveness.