• 제어로봇시스템학회논문지
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• 제20권6호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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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.

• 제어로봇시스템학회논문지
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• 제20권2호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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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.

• 인터넷정보학회논문지
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• 제10권3호
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• pp.173-185
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• 2009

본 논문에서는 두 가지 영상 콘트라스트 향상 기법인 RSWHE (Recursively Separated and Weighted Histogram Equalization)와 RSWHS (Recursively Separated and Weighted Histogram Specification)를 새롭게 제안한다. RSWHE는 히스토그램 평활화 방법에 히스토그램 분할과 가중치 개념을 적용하였고, RSWHS는 히스토그램 명세화 방법에 히스토그램 분할과 가중치 개념을 적용하였다. 제안 방법은 1) 입력 영상의 평균 명도 값을 기준으로 히스토그램을 분할하고, 2) 분할된 각 서브히스토그램(sub-histogram)이 차지하는 확률밀도 값을 계산하며, 3) 계산된 확률밀도 값을 가중치로 사용하여 각 서브히스토그램을 변형한 후, 4) 변형된 각 서브히스토그램을 독립적으로 평활화 하거나 (RSWHE 방법인 경우) 또는 명세화 하게 (RSWHS 방법인 경우) 된다. 다양한 영상에 대한 실험을 통하여, 제안하는 두 방법이 기존의 다른 방법들에 비하여 콘트라스트 향상과 평균 명도 보존 측면에서 우수한 성능을 나타냄을 알 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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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.

• 한국지능시스템학회논문지
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• 제23권1호
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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.

• IEIE Transactions on Smart Processing and Computing
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• 제3권2호
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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.

• 한국산학기술학회논문지
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• 제11권12호
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• pp.5127-5133
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• 2010

본 논문에서는 히스토그램 명세화에 기반을 둔 효과적인 영상 대비 개선 알고리즘을 제안한다. 히스토그램 평활화나 이로부터 파생된 방법들은 영상 대비 개선에 효과적인 도구로 사용되어 왔으나, 과도한 대비 개선이라는 부작용을 수반하는 결과를 자주 낳게 된다. 반면 기존의 히스토그램 명세화는 의도한 히스토그램을 얻기에 부적절하다는 단점을 가지고 있다. 본 논문에서는 의도한 히스토그램을 얻기 위해서 고주파필터를 활용한 방법을 제안한다. 제안한 방법은 기존의 영상 대비 방법에 대해서 향상된 화질을 제공할 뿐만 아니라, 영상의 통계적 속성에 적응적으로대응하는 속성을 보여주고 있다.

• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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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.