Contrast enhancement by using global and local histogram information jointly

Chien, Shih‐Chieh; Chang, Feng-Chia; Hua, Kai-Lung; Chen, I-Ying; Chen, Yung-Yao

doi:10.1109/aris.2017.8297188

Cited by 8 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the histogram of an image has a wide distribution, while it presents also extremely skewed local regions, the contrast in these regions should be improved. However, it would be more efficient to use the adaptive histogram equalization (Figure 3) rather than employing a global equalization that would offer a general brightness transformation and cannot properly adjust the contrast local regions situated in the dark background, for example [23]. The usage of the word "adaptive" emphasizes that specific regions from an image are addressed in a distinct way based on regional characteristics, and further that the method is expanded to the contrast-limited technique.…”

Section: Pixels and Histogramsmentioning

confidence: 99%

Modelling in Synthesis and Optimization of Active Vaccinal Components

et al. 2021

View full text Add to dashboard Cite

Cancer is the second leading cause of mortality worldwide, behind heart diseases, accounting for 10 million deaths each year. This study focusses on adenocarcinoma, which is a target of a number of anticancer therapies presently being tested in medical and pharmaceutical studies. The innovative study for a therapeutic vaccine comprises the investigation of gold nanoparticles and their influence on the immune response for the annihilation of cancer cells. The model is intended to be realized using Quantitative-Structure Activity Relationship (QSAR) methods, explicitly artificial neural networks combined with fuzzy rules, to enhance automated properties of neural nets with human perception characteristics. Image processing techniques such as morphological transformations and watershed segmentation are used to extract and calculate certain molecular characteristics from hyperspectral images. The quantification of single-cell properties is one of the key resolutions, representing the treatment efficiency in therapy of colon and rectum cancerous conditions. This was accomplished by using manually counted cells as a reference point for comparing segmentation results. The early findings acquired are conclusive for further study; thus, the extracted features will be used in the feature optimization process first, followed by neural network building of the required model.

show abstract

Section: Pixels and Histogramsmentioning

confidence: 99%

Modelling in Synthesis and Optimization of Active Vaccinal Components

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Subcategories of histogram equalization include global histogram equalization (GHE) [17], local histogram equalization (LHE) [18], and adaptive histogram equalization (AHE) [19]. Based on LHE and GHE, Chien et al presented a hybrid histogram equalization method [41], which can enhance regional details effectively. However, most modified HE algorithms easily distort visual information in processed images and tend to increase the contrast of background noise with a certain number of useless signals.…”

Section: Related Workmentioning

confidence: 99%

A Pulse-Number-Adjustable MSPCNN and Its Image Enhancement Application

et al. 2021

View full text Add to dashboard Cite

Pulse-coupled neural network (PCNN) aims to control neuronal firing state automatically and complete related image processing tasks. This paper presents a pulse-number-adjustable MSPCNN model (PNA-MSPCNN) that can automatically acquire the firing times and the firing frequency of each neuron.Hereinto, synaptic weight matrix Wijkl and decay factor  will generate an interaction value to determine the final calculation result of the internal activity U. Dynamic threshold amplitude V, step function Q, and auxiliary parameter P can precisely adjust the variation ranges of the dynamic threshold E. Additionally, we propose a low-light image enhancement method based on the above PNA-MSPCNN and a modified lowlight image enhancement (LIME). The proposed LIME algorithm focuses mainly on the parameter setting method of weight matrix Wmq, which will bring further improvement of testing image contrast. Experimental results demonstrate that our proposed method achieves better low-light image enhancement performances, compared to prevalent image enhancement methods, including SSIM of 0.8725, AMBE of 0.0550, MSE of 0.0092, and PSNR of 45.7764.

show abstract

“…Adaptive Histogram Equalization (AHE) [5], Dynamic Histogram Equalization (DHA) [6] improves the performance to some extent on pixel level by using local histogram but fails on non-uniform illumination images. Many others Global Histogram Equalization (GHE) [7] algorithm such as, Brightness Preserving Bi-Histogram Equalization (BPBHE) [8], BPDHE [9], DSIHE [10] and MMBEBHW [11] [12] are sensitive to noise are not able to enhance up to a level.…”

Section: ░ 1 Introductionmentioning

confidence: 99%

Contrast Enhancement of Colour Images by Optimized Fuzzy Intensification

Dixit

Yadav

Mishra

2021

IJEER

View full text Add to dashboard Cite

Contrast enhancement is a critical and difficult issue because inappropriate enhancement by existing global image enhancement techniques might result in over or under enhancement. Varying areas of the image that are lighted indicate different shades and contrast in the output images. Projected technique uses local colour correction in the Hue Saturation Luminance (HSL) colour space. To control colour fidelity in initial phase an optimized fuzzy intensification parameters are extracted automatically form fuzzy inference system for that particular image. Finally optimized Fuzzy Intensification parameter constants are used to minimize overexposed and underexposed areas and offers elevated contrast improvement. Several lab test conducted to analyze the effectiveness of the proposed method with existing strategies. Many quality evaluation parameters are evaluated, and findings are compared to some known colour picture contrast enhancement approaches. The produced output comparatively better than many existing techniques which support a moderate measure to visual perception of the processed images.

show abstract

Contrast enhancement by using global and local histogram information jointly

Cited by 8 publications

References 1 publication

Modelling in Synthesis and Optimization of Active Vaccinal Components

Modelling in Synthesis and Optimization of Active Vaccinal Components

A Pulse-Number-Adjustable MSPCNN and Its Image Enhancement Application

Contrast Enhancement of Colour Images by Optimized Fuzzy Intensification

Contact Info

Product

Resources

About