Image Enhancement Using Modified Histogram and Log-Exp Transformation

Zhuang, Liyun; Guan, Yuanyuan

doi:10.3390/sym11081062

Cited by 11 publications

(12 citation statements)

References 38 publications

(138 reference statements)

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“…The histogram accomplishes this by effectively distributing the most frequent intensity values. The histogram shows a graphical interpretation of the tonal intensity distributed in a digital image [41]. Usually, the distribution of its discrete intensity levels is within the range of 0 to L − 1, where L is the total number of gray levels in the image (typically 256).…”

Section: Equalization Of a Histogrammentioning

confidence: 99%

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

et al. 2021

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Infrared thermography is the science of measuring the infrared energy emitted by an object, translating it to apparent temperature variance, and displaying the result as an infrared image. Significantly, acquiring thermal images delivers distinctive levels of temperature differences in solar panels that correspond to their health status, which is beneficial for the early detection of defects. The proposed algorithm aims to analyze the thermal solar panel images. The acquired thermal solar panel images were segmented into solar cell sizes to provide more detailed information by region or cell area instead of the entire solar panel. This paper uses both the image histogram information and its corresponding cumulative distribution function (CDF), useful for image analysis. The acquired thermal solar panel images are enhanced using grayscale, histogram equalization, and adaptive histogram equalization to represent a domain that is easier to analyze. The experimental results reveal that the extraction results of thermal images provide better histogram and CDF features. Furthermore, the proposed scheme includes the convolutional neural network (CNN) for classifying the enhanced images, which shows that a 97% accuracy of classification was achieved. The proposed scheme could promote different thermal image applications—for example, non-physical visual recognition and fault detection analysis.

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Section: Equalization Of a Histogrammentioning

confidence: 99%

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

et al. 2021

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“…So, the gamma transform in this paper is used to correct LFS coefficients, highlight the contour characteristics of the reconstructed image, and improve the overall brightness of the degraded image. Gamma transform is completed by the following equation [31]:…”

Section: Gamma Transformmentioning

confidence: 99%

“…In order to objectively evaluate the effect of image enhancement, this paper adopts five indicators of Mean (image brightness) [15], mean local mean square error (MLMSE) (image contrast), peak signal to noise ratio (PSNR) (noise suppression level), mean local information entropy (MLIE) (information richness) [31], and structural similarity index measure (SSIM) (image distortion degree) [37] for performance evaluation and comparison. e objective metrics data of low illumination (Experiment 1), dust and spray (Experiment 2), and uneven lighting (Experiment 3) underground coal mine are shown in Tables 1-3.…”

Section: Objective Analysismentioning

confidence: 99%

Degraded Image Enhancement Using Dual-Domain-Adaptive Wavelet and Improved Fuzzy Transform

Fan

Huo

2021

Mathematical Problems in Engineering

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A novel enhancement algorithm for degraded image using dual-domain-adaptive wavelet and improved fuzzy transform is proposed, aiming at the problem of surveillance videos degradation caused by the complex lighting conditions underground coal mine. Firstly, the dual-domain filtering (DDF) is used to decompose the image into base image and detail image, and the contrast limited adaptive histogram enhancement (CLAHE) is adopted to adjust the overall brightness and contrast of the base image. Then, the discrete wavelet transform (DWT) is utilized to obtain the low frequency sub-band (LFS) and high frequency sub-band (HFS). Next, the wavelet shrinkage threshold is applied to calculate the wavelet threshold corresponding to the HFS at different scales. Meanwhile, a new Garrate threshold function that introduces adjustment factor and enhancement coefficient is designed to adaptively de-noise and enhance the HFS coefficients, and the Gamma function is employed to correct the LFS coefficients. Finally, the PAL fuzzy enhancement operator is improved and used to perform contrast enhancement and highlight area suppression on the reconstructed image to obtain an enhanced image. Experimental results show that the proposed algorithm can not only significantly improve the overall brightness and contrast of the degraded image but also suppresses the noise of dust and spray and enhances the image details. Compared with the similar algorithms of STFE, GTFE, CLAHE, SSR, MSR, DGR, and MSWT algorithms, the indicator values of comprehensive performance of the proposed algorithm are increased by 205%, 195%, 200%, 185%, 185%, 85%, 140%, and 215%, respectively. Moreover, compared with the other seven algorithms, the proposed algorithm has strong robustness and is more suitable for image enhancement in different mine environments.

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“…Through the weighted sum, mean brightness was preserved. Liyun Zhuang and Yepeng Guan [14] proposed the log-exponential method to compute the scale of gamma. The HE was modified through the gamma scale to show the richness in the information details.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Logarithmic-Power Algorithm for Preserving the Brightness in Contrast Distorted Images

Rekhi¹,

Sidhu²

2021

IJACSA

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Image Enhancement Using Modified Histogram and Log-Exp Transformation

Cited by 11 publications

References 38 publications

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

Degraded Image Enhancement Using Dual-Domain-Adaptive Wavelet and Improved Fuzzy Transform

Adaptive Logarithmic-Power Algorithm for Preserving the Brightness in Contrast Distorted Images

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