• Title/Summary/Keyword: Image Specification

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Multiresolution Histogram Specification Method in The Spatial Domain for Image Enhancement (영상 개선을 위한 공간 영역에서의 다해상도 히스토그램 지정 기법)

  • Park, Se-Hyuk;Huh, Kyung-Moo
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.169-171
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    • 2009
  • The histogram specification is to change the histogram shape of the image into the already defined shape. This technique can be applied usefully in various image processing fields which include a machine vision. However, the histogram specification technique has its basic limits. For example, the histogram does not have location information of pixel within the image and receives the digital image, which is stored through a quantization process, as an input. Namely, the accuracy of specification falls in the high-resolution image because the larger the resolution of image is becoming, the more the pixels having similar value are becoming. Therefore, we proposed the multiresolution histogram specification method for improving the accuracy of specification. Consequently, we can know that if the histogram specification is accomplished by using the proposed algorithm, destination image and source image were changed almost similarly.

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An Improved Histogram Specification using Multiresolution in the Spatial Domain for Image Enhancement (이미지 향상을 위해 공간영역에서 다중해상도를 이용한 개선된 히스토그램 특정화 방법)

  • Huh, Kyung-Moo
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.6
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    • pp.657-662
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    • 2014
  • Usually, spatial information can be incorporated into histograms by taking histograms of a multiresolution image. For these reasons, many researchers are interested in multiresolution histogram processing. If the relation and sensitivity of the multiresolution images are well combined without loss of information, we can obtain satisfactory results in several fields of image processing including histogram equalization, specification and pattern matching. In this paper, we propose a multiresolution histogram specification method that improves the accuracy of histogram specification. The multiresolution decomposition technique is used in order to overcome the unique feature of a histogram specification affected by a quantization error of a digitalized image. The histogram specification is processed after the reduction of image resolution in order to enhance the accuracy of the results by histogram specification methods. The experimental results show that the proposed method enhances the accuracy of specification compared to conventional methods.

Image Enhancement Based on Local Histogram Specification (로컬 히스토그램 명세화에 기반한 화질 개선)

  • Khusanov, Ulugbek;Lee, Chang-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.1
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    • pp.18-23
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    • 2013
  • In this paper we propose an image enhancement technique based on histogram specification method over local overlapping regions referred as Local Histogram Specification. First, both reference and original images are splitted into local regions that each overlaps half of its adjacent regions and general histogram specification method is used between corresponding local regions of reference and original image. However it produces noticeable boundary effects. Linear weighted image blending method is used to reduce this effect in order to make seamless image and we also proposed new technique dealing with over-enhanced contrast areas. We satisfied with our experimental results that showed better enhancement accuracy and less noise amplifications compared to other well-known image enhancement methods. We conclude that the proposed method is well suited for motion detection systems as a responsible part to overcome sudden illumination changes.

A Method of Improving Accuracy of Histogram Specification (정확성을 향상시킨 히스토그램 명세화 방법)

  • Huh, Kyung Moo
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.2
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    • pp.175-179
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    • 2014
  • The histogram specification turns the shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of the specification drops because of quantization errors of the digitized image. In this paper, we proposed a multiresolution histogram specification method in order to improve the accuracy of specification in terms of resemblance between destination and source image. The experimental results show that the proposed method enhances the accuracy of the specification compared to the conventional methods.

Automatic Histogram Specification Based on Fuzzy Membership Value for Image Enhancement (퍼지 멤버쉽 값을 이용한 히스토그램 명세화)

  • 황태호;이정훈
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.317-320
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    • 2002
  • In this paper, an automatic histogram specification method is proposed for image enhancement, Fuzzy membership value is adopted for the representation of image histogram. The desired PDF is automatically constructed by the fuzzy membership value. Fuzzy membership value is extracted from dark membership, bright membership function and original histogram. The effectual results are demonstrated by desired PDF which meet the image enhancement requirements. The performance and effectiveness are shown by the analysis and the resultant image in comparison with histogram equalization method.

Area Separation Histogram Specification Method for Accuracy Improvement of Vision Inspection (Vision 검사의 정확도 향상을 위한 영역 분할 히스토그램 지정 기법)

  • Park, Se-Hyuk;Huh, Kyung-Moo
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.431-433
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    • 2006
  • The goal of this paper is improvement of vision inspection accuracy by using histogram specification operation. The histogram is composed of horizontal axis of image intensity value and vertical axis of pixel number in image. In appearance vision inspection, the histogram of reference image and input image are different because of minutely lighting distinction. The minutely lighting distinction is main reason of vision inspection error in many cases. Therefore we made an effort for elevation of vision inspection accuracy by making the identical histogram of reference image and input image. As a result of this area separation histogram specification algorithm, we could increase the exactness of vision inspection and prevent system error from physical and spirit condition of human. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.

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Color Enhancement of Low Exposure Images using Histogram Specification and its Application to Color Shift Model-Based Refocusing

  • Lee, Eunsung;Kang, Wonseok;Kim, Sangjin
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.1
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    • pp.8-16
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    • 2012
  • An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

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Exact Histogram Specification Considering the Just Noticeable Difference

  • Jung, Seung-Won
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.2
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    • pp.52-58
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    • 2014
  • Exact histogram specification (EHS) transforms the histogram of an input image into the specified histogram. In the conventional EHS techniques, the pixels are first sorted according to their graylevels, and the pixels that have the same graylevel are further differentiated according to the local average of the pixel values and the edge strength. The strictly ordered pixels are then mapped to the desired histogram. However, since the conventional sorting method is inherently dependent on the initial graylevel-based sorting, the contrast enhancement capability of the conventional EHS algorithms is restricted. We propose a modified EHS algorithm considering the just noticeable difference. In the proposed algorithm, the edge pixels are pre-processed such that the output edge pixels obtained by the modified EHS can result in the local contrast enhancement. Moreover, we introduce a new sorting method for the pixels that have the same graylevel. Experimental results show that the proposed algorithm provides better image enhancement performance compared to the conventional EHS algorithms.

Image Contrast Enhancement based on Histogram Decomposition and Weighting (히스토그램 분할과 가중치에 기반한 영상 콘트라스트 향상 방법)

  • Kim, Ma-Ry;Chung, Min-Gyo
    • Journal of Internet Computing and Services
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    • v.10 no.3
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    • pp.173-185
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    • 2009
  • This paper proposes two new image contrast enhancement methods, RSWHE (Recursively Separated and Weighted Histogram Equalization) and RSWHS (Recursively Separated and Weighted Histogram Specification). RSWHE is a histogram equalization method based on histogram decomposition and weighting, whereas RSWHS is a histogram specification method based on histogram decomposition and weighting. The two proposed methods work as follows: 1) decompose an input histogram based on the image's mean brightness, 2) compute the probability for the area corresponding to each sub-histogram, 3) modify the sub-histogram by weighting it with the computed probability value, 4) lastly, perform histogram equalization (in the case of RSWHE) or histogram specification (in the case of RSWHS) on the modified sub-histograms independently. Experimental results show that RSWHE and RSWHS outperform other methods in terms of contrast enhancement and mean brightness preservation as well.

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DEVELOPMENT OF OPEN GIS COMPONENT SOFTWARE

  • Choi, Hae-Ock;Kim, Kwang-Soo;Lee, Jong-Hun
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.188-193
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    • 1999
  • Technology of GIS evolved as a means of assembling and analyzing diverse spatial data. Many systems have been developed, and almost of systems are proprietary. There is a lots of lack of interoperability and reusability between them. This paper describes the development of Open GIS component software. The developing system have an end in view of GIS tool software which is interoperable and reusable. To increase the interoperability and reusability, the system is based on the OGC(Open GIS Consortium)'s Open GIS Simple Features Specification for OLE/COM. The OGC's specification is announced to increasing the full interoperability of various geospatial data and geoprocessing resources. With the Open specification, component based software ensures the reusability. We implement three kinds of component: Geometry component, Spatial Reference System Component, and MapBase Component. The first two components are compatible to the OGC's specification and the third one is designed to GIS tool software for variant GIS applications. The Open GIS component software system is developed on object-oriented computing environment, ATL/COM and Visual C++. As we made application programs using Visual Basic, the advantages of component based Open GIS software was proved.

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