Performance Evaluation of Enhancement Algorithm for Contrast Distorted Images

Rekhi, Navleen Singh; Singh, Jasjit; Sidhu, Jagroop Singh; Arora, Amit

doi:10.1007/978-981-16-8826-3_4

Cited by 1 publication

(2 citation statements)

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“…The purpose of the EAGL is to extract detailed information to obtain better visibility of the image. Firstly, the original image is transformed into HSI (hue, saturation and intensity) channel [24]. Mostly, global mean, variance or entropy was used to estimate luminance.…”

Section: A Flow Diagram (Eagl)mentioning

confidence: 99%

“…Mostly, global mean, variance or entropy was used to estimate luminance. Since multi-resolution preserved the maximum amount of detail (energy), a 2Ddiscrete wavelet transforms at a scale level of '2' [24] is used to obtain luminance value from the intensity component of the input image. The scale value is computed by combining the scale-power function and Minkowski distance measure (MDM) from the contrast stretched and wavelet coefficients of the original image.…”

Section: A Flow Diagram (Eagl)mentioning

confidence: 99%

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EAGL: Enhancement Algorithm based on Gamma Correction for Low Visibility Images

Rekhi¹,

Sidhu²

2022

IJACSA

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Under poor light conditions or improper acquisition settings, the image degrades due to low contrast, poor brightness and suffer poor visual quality of the picture. An enhancement is required to manipulate the scale of pixel intensity for significant improvement in the image. This paper proposed the method of gamma correction with a self-adaptive value in accordance with the intensity scale of the image. After transformation to HSI (hue, saturation and intensity) channel, a multi-scale wavelet transform is implemented on the intensity component of the image. The gamma scale is computed from the combination of reformed scale constant of logarithm function and Minkowski distance measure. Lastly, wavelet based denoising technique is applied to suppress high noise coefficients to improve quality of the image. The proposed method is evaluated in terms of visual appearance, measure of information content, signal to noise ratio, and universal image quality index. It demonstrated that the proposed method showed its efficacy in terms of quality and improved visibility.

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Section: A Flow Diagram (Eagl)mentioning

confidence: 99%

Section: A Flow Diagram (Eagl)mentioning

confidence: 99%