Implementation of Single Image Histogram Equalization and Contrast Enhancement on Zynq FPGA

2021 ◽  
pp. 75-82
Author(s):  
Prathap Soma ◽  
Chundru Sravanthi ◽  
Palaparthi Srilakshmi ◽  
Ravi Kumar Jatoth
Keyword(s):  
Contrast Enhancement ◽  
Histogram Equalization ◽  
Single Image ◽  
Image Histogram

scholarly journals Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3110
Author(s):  
Julio César Mello Román ◽  
Vicente R. Fretes ◽  
Carlos G. Adorno ◽  
Ricardo Gariba Silva ◽  
José Luis Vázquez Noguera ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Mathematical Morphology ◽  
Panoramic Radiography ◽  
Histogram Equalization ◽  
Dental Radiography ◽  
Panoramic Radiographs ◽  
Image Histogram ◽  
Multi Scale ◽  
Dental Radiographs

Panoramic dental radiography is one of the most used images of the different dental specialties. This radiography provides information about the anatomical structures of the teeth. The correct evaluation of these radiographs is associated with a good quality of the image obtained. In this study, 598 patients were consecutively selected to undergo dental panoramic radiography at the Department of Radiology of the Faculty of Dentistry, Universidad Nacional de Asunción. Contrast enhancement techniques are used to enhance the visual quality of panoramic dental radiographs. Specifically, this article presents a new algorithm for contrast, detail and edge enhancement of panoramic dental radiographs. The proposed algorithm is called Multi-Scale Top-Hat transform powered by Geodesic Reconstruction for panoramic dental radiography enhancement (MSTHGR). This algorithm is based on multi-scale mathematical morphology techniques. The proposal extracts multiple features of brightness and darkness, through the reconstruction of the marker (obtained by the Top-Hat transformation by reconstruction) starting from the mask (obtained by the classic Top-Hat transformation). The maximum characteristics of brightness and darkness are added to the dental panoramic radiography. In this way, the contrast, details and edges of the panoramic radiographs of teeth are improved. For the tests, MSTHGR was compared with the following algorithms: Geodesic Reconstruction Multiscale Morphology Contrast Enhancement (GRMMCE), Histogram Equalization (HE), Brightness Preserving Bi-Histogram Equalization (BBHE), Dual Sub-Image Histogram Equalization (DSIHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Quadri-Histogram Equalization with Limited Contrast (QHELC), Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction (GC). Experimentally, the numerical results show that the MSTHGR obtained the best results with respect to the Contrast Improvement Ratio (CIR), Entropy (E) and Spatial Frequency (SF) metrics. This indicates that the algorithm performs better local enhancements on panoramic radiographs, improving their details and edges.

Entropy based Range Optimized Brightness Preserved Histogram-Equalization for Image Contrast Enhancement

2016 ◽  
Vol 6 (1) ◽  
pp. 59-72 ◽  
Author(s):  
Krishna Gopal Dhal ◽  
Sankhadip Sen ◽  
Kaustav Sarkar ◽  
Sanjoy Das
Keyword(s):  
Contrast Enhancement ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Image Contrast ◽  
Experimental Results ◽  
Signal To Noise ◽  
Image Histogram ◽  
Image Contrast Enhancement ◽  
Noise Ratio

In this study the over-enhancement problem of traditional Histogram-Equalization (HE) has been removed to some extent by a variant of HE called Range Optimized Entropy based Bi-Histogram Equalization (ROEBHE). In ROEBHE image histogram has been thresholded into two sub-histograms i.e. histograms corresponding to background and foreground. The threshold is calculated by maximizing the sum of the entropy of these two sub-histograms. The range for equalization has been optimized by maximizing the Peak-Signal to Noise ratio (PSNR). The experimental results prove that ROEBHE has prevailed over existing methods and PSNR is a better range optimizer than Absolute Mean Brightness Error (AMBE).

An Enhancement of Multi Classifiers Voting Method for Mammogram Image based on Image Histogram Equalization

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
Ashraf Osman Ibrahim ◽  
◽  
Ali Ahmed ◽  
Anik Hanifatul Azizah ◽  
Saima Anwar Lashar ◽  
...  
Keyword(s):  
Histogram Equalization ◽  
Image Histogram ◽  
Mammogram Image ◽  
Voting Method

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

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