• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.3245-3271
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• 2016

To obtain well-dehazed images at the receiver while sustaining low bit rates in the transmission pipeline, this paper investigates the effects of image dehazing methods using dehazing contrast-enhancement filters on image compression for surveillance systems. At first, this paper proposes a novel image dehazing method by using a new method of calculating the transmission function—namely, the direct denoising method. Next, we deduce the dehazing effects of the direct denoising method and image dehazing method based on dark channel prior (DCP) on image compression in terms of ringing artifacts and blocking artifacts. It can be concluded that the direct denoising method performs better than the DCP method for decompressed (reconstructed) images. We also improve the direct denoising method to obtain more desirable dehazed images with higher contrast, using the saliency map as the guidance image to modify the transmission function. Finally, we adjust the parameters of dehazing contrast-enhancement filters to obtain a corresponding composite peak signal-to-noise ratio (CPSNR) and blind image quality assessment (BIQA) of the decompressed images. Experimental results show that different filters have different effects on image compression. Moreover, our proposed dehazing method can strike a balance between image dehazing and image compression.

• 전자공학회논문지 IE
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• 제46권4호
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• pp.31-41
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• 2009

최근에 널리 보급되고 있는 디지털 카메라는 제한된 크기의 Dynamic Range를 갖는 이미지 센서의 한계로 인하여 Dynamic Range가 넓은 환경에서 영상을 획득하면 인간의 눈으로 보는 것과는 달리 밝게 포화된 영상 또는 노출이 적은 어두운 영상을 얻게 된다. 입력 영상의 Dynamic Range를 압축하고 Contrast를 개선하기 위한 여러 가지 디지털 영상 처리 방법들 중에서 인간의 시각모델을 기반으로 한 Retinex 알고리즘은 Contrast 향상 및 컬러 재현성에 있어서 매우 효과적인 방법으로 알려져 있다. 하지만, Retinex 알고리즘은 Dynamic Range가 넓은 환경에서 획득한 영상의 경우에 전역적인 Contrast는 증가 하나 국부적인 Contrast가 오히려 감소하는 Contrast 불균형이 발생하는 문제가 있다. 이러한 문제를 개선하기 위해 본 논문에서는 Retinex 영상에서 에지 정보와 노출 정보를 추출하여 가중치 맵을 구성하고 이를 영상 한성과정에 적용하여 Contrast의 불균형을 개선하는 알고리즘을 제안한다. 실험 결과 영상의 비교와 수치 분석을 통해 제안된 알고리즘이 기존의 알고리즘에 비해 Contrast 향상 성능이 더 우수한 방법임을 확인하였다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.1160-1163
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• 2009

Many researches showed that perceived image contrast increases as the relative surround luminance increases. However, most experiments were conducted under limited surround conditions. In this research, a psychophysical experiment was conducted to investigate the change in perceived image contrast under wide range of surround luminance up to 1820 cd/$m^2$. A large area illuminator was used as a backlight. It consists of 23 dimmable fluorescent lamps and a sheet of diffuser. The luminance could be adjusted to 7 different surround ratios: 0, 0.3, 0.56, 0.96, 2.24, 5.81, and 9.99. Results showed that perceived image contrast changes as a typical band-pass shape and the maximum contrast is found near $S_R$=1.

• Journal of Information Technology Applications and Management
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• 제25권2호
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• pp.41-52
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• 2018

This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

• 한국멀티미디어학회논문지
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• 제15권12호
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• pp.1409-1416
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• 2012

An image segmentation result depends on pre-processing steps such as contrast enhancement, edge detection, and smooth filtering etc. Especially medical images are low contrast and contain some noises. Therefore, the contrast enhancement and noise removal techniques are required in the pre-processing. In this study, we present an extension by a novel histogram equalization in which both local and global contrast is enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Most important is that original image information can be used for both global brightness preserving and local contrast enhancement, and image quality improvement filtering. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

• 한국통신학회논문지
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• 제38A권11호
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• pp.928-937
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• 2013

본 논문은 특이값 분해와 영상 피라미드를 이용한 새로운 대비 개선 방법을 제안한다. 제안된 방법은 다음과 같이 네 단계로 진행 된다. 먼저 전역 명암대비와 지역적 디테일을 향상시키기 위해 영상 피라미드를 이용하여 영상을 기저영상과 세부영상들로 분해한다. 전역 명암대비 향상은 특이값 분해를 이용하여 영상 전체의 명암대비를 향상시키고, 지역적 디테일 향상은 가중치를 이용하여 개선시킨다. 영상 합성은 영상의 컬러 일관성을 유지하기 위해 컬러와 명암성분들을 결합한다. 실험 결과를 통해 제안된 방법은 기존의 방법들보다 영상의 세부 정보를 강화하면서 전체적인 명암대비 개선을 보인다.

• ETRI Journal
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• 제41권6호
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• pp.797-810
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• 2019

Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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• pp.1139-1142
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• 2007

In this paper, an image enhancement method by saturation and contrast improvement is proposed. Histogram equalization with color difference makes higher contrast. By generating saturation amplification ratio with color difference, the saturation improves effectively. The experimental results show that the proposed algorithm has higher contrast and more natural - look than the conventional methods.

• 대한디지털의료영상학회논문지
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• 제7권1호
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• pp.7-13
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• 2005

Purpose : Image plate (IP) is substituted for film in computed radiography. This study is to investigate into a variation of contrast and detail by the number used of image plate in computed radiography. Materials and Methods : A Contrast-Detail(CD)-RAD 2.0 phantom(Nijmegen hospital, The Netherlands) was used for this study. The computed radiography(CR) CD-RAD phantom images were acquired at 40 kVp, 160 mA, 1.6 mAs, and small focus with the Shimadzu general radiography UD-150B-10 system and Fuji FCR 5000 image process system with speed of 200. The IP used including once, 5000 times, and 10000 times also was used. The numerical value of image quality figures (IQF) was produced by CD-RAD analyser(the program is installed in the directory), and then contrast-detail curve was drawn. Results : In this study, the value of IQF was 3.53 in IP used once, 3.40 in 5000 times, and 3.22 in 10000 times. Conclusions : There was a variation of contrast-detail curve by the number used of IP with contrast-detail phantom in computed radiography. Therefore, it is necessary that the IP with lower IQF and a shift of contrast-detail curve to the lower left part is used.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권4호
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• pp.840-866
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• 2014

Visibility in underwater images is usually poor because of the attenuation of light in the water that causes low contrast and color variation. In this paper, a new approach for underwater image quality improvement is presented. The proposed method aims to improve underwater image contrast, increase image details, and reduce noise by applying a new method of using contrast stretching to produce two different images with different contrasts. The proposed method integrates the modification of the image histogram in two main color models, RGB and HSV. The histograms of the color channel in the RGB color model are modified and remapped to follow the Rayleigh distribution within certain ranges. The image is then converted to the HSV color model, and the S and V components are modified within a certain limit. Qualitative and quantitative analyses indicate that the proposed method outperforms other state-of-the-art methods in terms of contrast, details, and noise reduction. The image color also shows much improvement.