Survey on illumination condition of video / image under heterogeneous environments for enhancement

Akila, K.; Chitrakala, S.; Vaishnavi, S.

doi:10.1109/icaccs.2016.7586389

Cited by 3 publications

(2 citation statements)

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“…In accordance with literature reviews provided over the years, several methods for improving images' contrast and illumination have been proposed. Previous survey studies, such [2]- [4], [6], [7], [10], [11], [17], [20], [28]- [31], reported that HE and GT are the most involved techniques in proposed contrast and illumination enhancement methods given their simplicity, fast processing time and high performance.…”

Section: Related Workmentioning

confidence: 99%

“…However, they may damage edges and produce over-enhancement and uneven brightness levels. Frequency-domain methods use a Fourier transform of an image to be multiplied by a high-frequency modulation filter and then perform inverse transformation to produce an enhanced image [2], [20], [21]. Such methods can improve image details and noise but require complex calculations and manual input parameters.…”

Section: Introductionmentioning

confidence: 99%

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Brightness and Contrast Enhancement Method for Color Images Via Pairing Adaptive Gamma Correction and Histogram Equalization

Bataineh¹

2023

IJACSA

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For enhanced adaptability to poor light enhancement whilst achieving high image contrast, a new method for color image correction based on the advantages of non-linear function in grey transformation and histogram equalization techniques is proposed in this work. Firstly, the original red, green and blue (RGB) image is converted into the HSV color space, and the V channel is used for enhancement. An adaptive gamma generator is proposed to adaptively calculate gamma parameters in accordance with dark, medium, or bright image conditions. The computed gamma parameters are used to propose a cumulative distribution function that produces an optimized curve for illumination values. Next, a second modified equalization is performed to evenly correct the offset of the illumination curve values on the basis of the equal probability of the available values only. Finally, the processed V channel replaces the original V channel, and the new HSV model returns to the RGB color space. Experiments show that the proposed method can significantly improve the low contrast and poor illumination of the color image whilst preserving the color and details of the original image. Results from benchmark data sets and measurements indicate that the proposed method outperforms other state-of-the-art methods.

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