• Title/Summary/Keyword: Over-enhancement

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Histogram Equalization Algorithm for Suppressing Over-Enhancement and Enhancing Edges (과대 대조 강조 방지 및 엣지 강화를 동시에 수행하는 히스토그램 평활화 알고리듬)

  • Mun, Junwon;Kim, Jaeseok
    • Journal of Korea Multimedia Society
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    • v.22 no.9
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    • pp.983-991
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    • 2019
  • Histogram equalization method is a popular contrast enhancement technique. However, there are some drawbacks, namely, over-enhancement, under-enhancement, structure information loss, and noise amplification. In this paper, we propose an edge-enhancing histogram equalization algorithm while suppressing over-enhancement simultaneously. Firstly, over-enhancement is suppressed by clipping a transfer function, then, edge enhancement is achieved by using guided image filter. Experiments are carried out to evaluate the performance of the various HE algorithms. As a result, both qualitative and quantitative assessment showed that the proposed algorithm successfully suppressed over-enhancement while enhancing edges.

Robust speech quality enhancement method against background noise and packet loss at voice-over-IP receiver (배경잡음 및 패킷손실에 강인한 voice-over-IP 수신단 기반 음질향상 기법)

  • Kim, Gee Yeun;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.37 no.6
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    • pp.512-517
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    • 2018
  • Improving voice quality is a major concern in telecommunications. In this paper, we propose a robust speech quality enhancement against background noise and packet loss at VoIP (Voice-over-IP) receiver. The proposed method combines network jitter estimation based on hybrid Markov chain, adaptive playout scheduling using the estimated jitter, and speech enhancement based on restoration of amplitude and phase to enhance the quality of the speech signal arriving at the VoIP receiver over IP network. The experimental results show that the proposed method removes the background noise added to the speech signal before encoding at the sender side and provides the enhanced speech quality in an unstable network environment.

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.

An Enhancement of Image Segmentation Using Modified Watershed Algorithm

  • Kwon, Dong-Jin
    • International journal of advanced smart convergence
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    • v.11 no.4
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    • pp.81-87
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    • 2022
  • In this paper, we propose a watershed algorithm that applies a high-frequency enhancement filter to emphasize the boundary and a local adaptive threshold to search for minimum points. The previous method causes the problem of over-segmentation, and over- segmentation appears around the boundary of the object, creating an inaccurate boundary of the region. The proposed method applies a high-frequency enhancement filter that emphasizes the high-frequency region while preserving the low-frequency region, and performs a minimum point search to consider local characteristics. When merging regions, a fixed threshold is applied. As a result of the experiment, the proposed method reduced the number of segmented regions by about 58% while preserving the boundaries of the regions compared to when high frequency emphasis filters were not used.

GAN-Based Local Lightness-Aware Enhancement Network for Underexposed Images

  • Chen, Yong;Huang, Meiyong;Liu, Huanlin;Zhang, Jinliang;Shao, Kaixin
    • Journal of Information Processing Systems
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    • v.18 no.4
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    • pp.575-586
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    • 2022
  • Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.

Spatial Contrast Enhancement using Local Statistics based on Genetic Algorithm

  • Choo, MoonWon
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.89-92
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    • 2017
  • This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

An Adaptive Image Enhancement Algorithms Using Saturation Improvement (채도 향상을 이용한 적응형 화질 개선 알고리듬)

  • Jo, Young-Sim;Yun, Jong-Ho;Park, Jin-Sung;Choi, Myung-Ryul
    • Journal of Korea Multimedia Society
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    • v.9 no.11
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    • pp.1455-1464
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    • 2006
  • In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.

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A Comprehensive and Practical Image Enhancement Method

  • Wu, Fanglong;Liu, Cuiyin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5112-5129
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    • 2019
  • Image enhancement is a challenging problem in the field of image processing, especially low-light color images enhancement. This paper proposed a robust and comprehensive enhancement method based several points. First, the idea of bright channel is introduced to estimate the illumination map which is used to attain the enhancing result with Retinex model, and the color constancy is keep as well. Second, in order eliminate the illumination offsets wrongly estimated, morphological closing operation is used to modify the initial estimating illumination. Furthermore, in order to avoid fabricating edges, enlarged noises and over-smoothed visual features appearing in enhancing result, a multi-scale closing operation is used. At last, in order to avoiding the haloes and artifacts presented in enhancing result caused by gradient information lost in previous step, guided filtering is introduced to deal with previous result with guided image is initial bright channel. The proposed method can get good illumination map, and attain very effective enhancing results, including dark area is enhanced with more visual features, color natural and constancy, avoiding artifacts and over-enhanced, and eliminating Incorrect light offsets.

An Adaptive Color Enhancement Algorithm using the Preferred Color Reconstruction (선호색 보정을 이용한 화질 향상 알고리즘)

  • Yang, Kyoung-Ok;Hwang, Bo-Hyun;Lee, Seung-Jun;Yun, Jong-Ho;Chon, Myung-Ryul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.57 no.1
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    • pp.22-29
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    • 2008
  • In this paper, we propose an adaptive color enhancement algorithm. It is used for the flat panel displays (FPDs) such as LCD, PDP, and so on. The proposed algorithm consists of an adaptive linear approximation CDF(Cumulative Density Function) algorithm and an adaptive saturation enhancement algorithm. The one is for contrast enhancement which prevents an image from the distortion by luminance transient of an input image. The other is the algorithm which improves the saturation without the contour artifact and over-saturation, whose problems are generated during the enhancing saturation. In addition, it allows to achieve the high quality image using the saturation enhancement method for a preferred color of original image. Visual test and standard deviation of their histograms have been applied to evaluate the resultant output images of the proposed algorithm.

Local Enhancement Mechanism of Cold Surges over the Korean Peninsula (한반도 한파의 지역적 강화 메커니즘)

  • Lee, Hye-Young;Kim, Joowan;Park, In-Gyu;Kang, Hyungyu;Ryu, Hosun
    • Atmosphere
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    • v.28 no.4
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    • pp.383-392
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    • 2018
  • This study investigates synoptic characteristics of cold surges over South Korea during winter season (December-February). A total of 63 cold events are selected by quantile regression analysis using daily mean temperature observations from 11 KMA stations for 38 years (1979/80-2016/17). Large-scale pressure pattern during the cold surges is well characterized by high over Siberia and low over Aleutian regions, which elucidates cold advection over the Korean peninsula. However, the large-scale pattern cannot successfully explain the observed sudden decrease of temperature during the cold surges. Composite analyses reveal that a synoptic-scale cyclone developing over the northern Japan is a key feature that significantly contribute to the enhancement of cold advection by increasing pressure gradient over the Korean peninsula. Enhanced sensible and latent heat fluxes are observed over the southern ocean of Korea and Japan during the cold surges due to temperature and humidity differences between the near surface and the lower atmosphere over the ocean. The evaporated water vapor transported toward the center of the surface cyclone and condenses in the lower-to-middle troposphere. The released energy likely promotes the development of the surface cyclone by inducing positive PV near the surface of the heating region.