Contextual and Variational Contrast Enhancement

Çelik, Turgay; Tjahjadi, Tardi

doi:10.1109/tip.2011.2157513

Cited by 397 publications

(199 citation statements)

References 20 publications

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“…In this section, the results of the proposed technique has been compared to the existing state-of-the-art image enhancement techniques, namely HE [2], AEHS [19], CVC [25], LDR [24], WAHE [16], CACD [17], AGCWD [9], and RSWHE [8]. The comparison has been performed in both qualitative and quantitative manner.…”

Section: Resultsmentioning

confidence: 99%

“…AEHS is proposed for both local and global contrast enhancement whereas DHS uses differential information from an input histogram to eliminate the annoying side effects. Besides the aforementioned enhancement methods, there exist few other methods such as guided image contrast enhancement [21] and image enhanccement by entropy maximization [22], contrast enhancement based on piecewise linear transformation (PLT) [23], layered difference representation (LDR) [24], and inter pixel contextual information (named as CVC) [25]. LDR first divides the gray levels of an image into different layers and makes a tree structure for deriving a transformation function.…”

Section: Introductionmentioning

confidence: 99%

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A histogram specification technique for dark image enhancement using a local transformation method

Hussain

Rahman

et al. 2018

IPSJ T Comput Vis Appl

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Traditional image enhancement techniques produce different types of noise such as unnatural effects, over-enhancement, and artifacts, and these drawbacks become more prominent in enhancing dark images. To overcome these drawbacks, we propose a dark image enhancement technique where local transformation of the pixels have been performed. Here, we apply a transformation method of different parts of the histogram of an input image to get a desired histogram. Afterwards, histogram specification technique has been done on the input image using this transformed histogram. The performance of the proposed technique has been evaluated in both qualitative and quantitative manner, which shows that the proposed method improves the quality of the image with minimal unexpected artifacts as compared to the other techniques.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A histogram specification technique for dark image enhancement using a local transformation method

Hussain

Rahman

et al. 2018

IPSJ T Comput Vis Appl

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“…To solve this problem, local enhancement techniques are proposed where transformation of an image pixel depends on the neighboring pixels' information. Hence, it lacks global brightness information and may result in local artifacts [11]. Moreover, the computational complexities of these methods are large as compared to that of global enhancement techniques.…”

Section: Introductionmentioning

confidence: 99%

An adaptive gamma correction for image enhancement

Rahman

Abdullah-Al-Wadud

et al. 2016

J Image Video Proc.

221

123

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Due to the limitations of image-capturing devices or the presence of a non-ideal environment, the quality of digital images may get degraded. In spite of much advancement in imaging science, captured images do not always fulfill users' expectations of clear and soothing views. Most of the existing methods mainly focus on either global or local enhancement that might not be suitable for all types of images. These methods do not consider the nature of the image, whereas different types of degraded images may demand different types of treatments. Hence, we classify images into several classes based on the statistical information of the respective images. Afterwards, an adaptive gamma correction (AGC) is proposed to appropriately enhance the contrast of the image where the parameters of AGC are set dynamically based on the image information. Extensive experiments along with qualitative and quantitative evaluations show that the performance of AGC is better than other state-of-the-art techniques.

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“…However this technique is also having some side effects. In [21] Celik and Jahjadi proposed contextual and variational contrast enhancement for image. This algorithm enhances the contrast of an input image using interpixel contextual information.…”

Section: Introductionmentioning

confidence: 99%

Automatic Method for Contrast Enhancement of Natural Color Images

Lal¹,

Narasimhadhan²,

Kumar³

2015

Journal of Electrical Engineering and Technology

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-The contrast enhancement is great challenge in the image processing when images are suffering from poor contrast problem. Therefore, in order to overcome this problem an automatic method is proposed for contrast enhancement of natural color images. The proposed method consist of two stages: in first stage lightness component in YIQ color space is normalized by sigmoid function after the adaptive histogram equalization is applied on Y component and in second stage automatic color contrast enhancement algorithm is applied on output of the first stage. The proposed algorithm is tested on different NASA color images, hyperspectral color images and other types of natural color images. The performance of proposed algorithm is evaluated and compared with the other existing contrast enhancement algorithms in terms of colorfulness metric and color enhancement factor. The higher values of colorfulness metric and color enhancement factor imply that the visual quality of the enhanced image is good. Simulation results demonstrate that proposed algorithm provides higher values of colorfulness metric and color enhancement factor as compared to other existing contrast enhancement algorithms. The proposed algorithm also provides better visual enhancement results as compared with the other existing contrast enhancement algorithms.

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Contextual and Variational Contrast Enhancement

Cited by 397 publications

References 20 publications

A histogram specification technique for dark image enhancement using a local transformation method

A histogram specification technique for dark image enhancement using a local transformation method

An adaptive gamma correction for image enhancement

Automatic Method for Contrast Enhancement of Natural Color Images

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