A Reversible Contrast Enhancement Scheme For Color Images

Guan, Zhihao; Wu, Haotian

doi:10.1109/icme46284.2020.9102950

Cited by 7 publications

(3 citation statements)

References 18 publications

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“…The number of shifts N was varied from 10 to 40 in increments of 10 to match the experimental condition of the compared method. In this section, we compare our method with Guan [13] and Nishikawa's methods [14].…”

Section: Resultsmentioning

confidence: 99%

Near Hue-Preserving Reversible Contrast and Saturation Enhancement Using Histogram Shifting

KUROKAWA

Yamato

Hasegawa

2022

IEICE Trans. Inf. & Syst.

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In recent years, several reversible contrast-enhancement methods for color images using digital watermarking have been proposed. These methods can restore an original image from a contrast-enhanced image, in which the information required to recover the original image is embedded with other payloads. In these methods, the hue component after enhancement is similar to that of the original image. However, the saturation of the image after enhancement is significantly lower than that of the original image, and the obtained image exhibits a pale color tone. Herein, we propose a method for enhancing the contrast and saturation of color images and nearly preserving the hue component in a reversible manner. Our method integrates red, green, and blue histograms and preserves the median value of the integrated components. Consequently, the contrast and saturation improved, whereas the subjective image quality improved. In addition, we confirmed that the hue component of the enhanced image is similar to that of the original image. We also confirmed that the original image was perfectly restored from the enhanced image. Our method can contribute to the field of digital photography as a legal evidence. The required storage space for color images and issues pertaining to evidence management can be reduced considering our method enables the creation of color images before and after the enhancement of one image.

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Section: Resultsmentioning

confidence: 99%

Near Hue-Preserving Reversible Contrast and Saturation Enhancement Using Histogram Shifting

KUROKAWA

Yamato

Hasegawa

2022

IEICE Trans. Inf. & Syst.

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“…The requirement on quality is particularly important in steganography, which aims to secretly embed a large payload [2]. Other applications have different requirements, for example, the survival of the embedded data as in the application of watermarking [20], quick data extraction for continuous authentication [25], and reversibility for handling sensitive content or rare artwork [9]. However, increased payload usually leads to image distortion or quality degradation.…”

Section: Introductionmentioning

confidence: 99%

CUPSEED - A combined use of prediction syntax elements to embed data in SHVC video

Pang

Tew

Wong

et al. 2021

Multimed Tools Appl

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With the rapid advancement in digital technologies, video rises to become one of the most effective communication tools that continues to gain popularity and importance. As a result, various proposals are put forward to manage videos, and one of them is data embedding. Essentially, data embedding inserts data into the video to serve a specific purpose, including proof of ownership via watermark, covert communication in steganography, and authentication via fragile watermark. However, most conventional methods embed data by using only one type of syntax element defined in the video coding standard, which may suffer from large bit rate overhead, quality degradation, or low payload. Therefore, this work aims to explore the combined use of multiple prediction syntax elements in SHVC for the purpose of data embedding. Specifically, the intra prediction mode, motion vector predictor, motion vector difference, merge mode and coding block structure are collectively manipulated to embed data. The experimental results demonstrate that, in comparison to the conventional single-venue data embedding methods, the combined use of prediction syntax elements can achieve higher payload while preserving the perceptual quality with minimal bit rate variation. In the best case scenario, a total of 556.1 kbps is embedded into the video sequence PartyScene with a drop of 0.15 dB in PSNR while experiencing a bit rate overhead of 7.4% when all prediction syntax elements are utilized altogether. A recommendation is then put forward to choose specific types of syntax element for data embedding based on the characteristics of the video.

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“…An improved method was proposed in [20] to resolve the inability to achieve complete image recovery. The proposed method similarly converts the RGB channels to Max, Median, and Min channels and applies a CE method on the Max channel.…”

Section: Introductionmentioning

confidence: 99%

A Bi-Histogram Shifting Contrast Enhancement for Color Images

Amoah¹,

Kwabena²

2021

Journal of Quantum Computing

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Recent contrast enhancement (CE) methods, with a few exceptions, predominantly focus on enhancing gray-scale images. This paper proposes a bihistogram shifting contrast enhancement for color images based on the RGB (red, green, and blue) color model. The proposed method selects the two highest bins and two lowest bins from the image histogram, performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked images. The proposed method simultaneously performs both right histogram shifting (RHS) and left histogram shifting (LHS) in each histogram shifting repetition to embed and split the highest bins while combining the lowest bins with their neighbors to achieve histogram equalization (HE). The least maximum number of histograms shifting repetitions among the three RGB channels is used as the default number of histograms shifting repetitions performed to enhance original images. Compared to an existing contrast enhancement method for color images and evaluated with PSNR, SSIM, RCE, and RMBE quality assessment metrics, the experimental results show that the proposed method's enhanced images are visually and qualitatively superior with a more evenly distributed histogram. The proposed method achieves higher embedding capacities and embedding rates in all images, with an average increase in embedding capacity of 52.1%.

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A Reversible Contrast Enhancement Scheme For Color Images

Cited by 7 publications

References 18 publications

Near Hue-Preserving Reversible Contrast and Saturation Enhancement Using Histogram Shifting

Near Hue-Preserving Reversible Contrast and Saturation Enhancement Using Histogram Shifting

CUPSEED - A combined use of prediction syntax elements to embed data in SHVC video

A Bi-Histogram Shifting Contrast Enhancement for Color Images

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