Optimally sectioned and successively reconstructed histogram sub-equalization based gamma correction for satellite image enhancement

Singh, Himanshu; Kumar, Arun; Balyan, L. K.; Lee, Heung-No

doi:10.1007/s11042-019-7383-0

Cited by 18 publications

(4 citation statements)

References 25 publications

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“…This method improves images, but the results are unsatisfactory. In [47], a method to improve dark images is proposed. This method uses both the non-linear gamma function and the local HE method as steps in the algorithm.…”

Section: Related Workmentioning

confidence: 99%

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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Section: Related Workmentioning

confidence: 99%

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

Bataineh¹

2023

IJACSA

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“…The position of segmentation points has been determined using the modified 2D histogram and the author claim that it performs excellent brightness preservation and contrast. For satisfactory enhancement, a highly adaptive gamma value-set can be derived in (Singh et al, 2019 ). The robustness of this algorithm improved because of its adaptive behavior and it is more capable for covering different variety of images.…”

Section: Introductionmentioning

confidence: 99%

Image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) for low exposure image enhancement

Acharya

Kumar

2022

Multidim Syst Sign Process

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In this paper, a novel image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) technique is proposed for the enhancement of low exposure images. The proposed method involves, computation of the histogram which includes a new approach of image sub-division, enhancement controlling mechanism, modification of probability density function (PDF) and histogram equalization (HE). The original histogram is segmented into sub-histograms based on exposure threshold and mean, to preserve the brightness and entropy. Then, individual sub-histogram is clipped separately to control the enhancement rate. For enhancing the visual quality, HE is applied to individual sub-histogram using the modified PDF. The experimental results show that, the proposed ISQCAHE method avoids the unpleasant artifacts effectively and provide a natural appearance to the enhanced image. It is simple, adaptive and performs superior than other techniques in terms of visual quality, absolute mean brightness error, entropy, Natural image quality evaluation, brightness preservation, structure similarity index measure and feature similarity index measure.

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“…Histogram Equalization (HE) [1] is one of the most widely used methods in image enhancement [2][3][4][5] , which has the advantages of easy computation and implementation [6] . Nevertheless, the result after histogram equalization brings about some disadvantages [7] such as mean gray value's fixing, entropy's declination, and the details' missing.…”

Section: Introductionmentioning

confidence: 99%

Three Adaptive Sub-Histograms Equalization Algorithm for Maritime Image Enhancement

et al. 2020

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According to maritime image histograms' statistic and analysis, the histogram of pure maritime image obeys Gaussian distribution approximately, thus Three Adaptive Sub-histograms Equalization (TASHE) algorithm for maritime image enhancement is proposed in this paper. First, the characteristics of pure maritime image's histogram are studied, then the adaptive threshold's optimal selection strategy for the histogram's division is discussed, finally the implement of three sub-histograms is described. This paper employs visible gray maritime image, visible color maritime image and infrared maritime image to verify the enhancement algorithm's effectiveness and robustness, the experimental results show that TASHE algorithm can not only keep the maritime image's mean brightness and naturalness, but also improve the maritime image's contrast without the noise and artifacts. The objective image quality assessment also indicates that TASHE algorithm can improve the original maritime image's Enhancement Measure by Entropy (EME) value, furthermore, when a maritime image is pre-processed by TASHE algorithm, the maritime target's Detection Rate (DR) can be improved.

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Optimally sectioned and successively reconstructed histogram sub-equalization based gamma correction for satellite image enhancement

Cited by 18 publications

References 25 publications

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

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

Image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) for low exposure image enhancement

Three Adaptive Sub-Histograms Equalization Algorithm for Maritime Image Enhancement

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