Histogram Equalization for Image Enhancement Using Kidney Ultrasound Images
Medical image processing plays an essential role in providing information in wide area for such advanced images. Kidney Ultrasound image (KUI) is an advanced medical imaging technique providing rich information about the size, shape, and location of the kidneys. KUI obtained from Doppler technique colored coded vessels is a valuable tool to help physicians to diagnose and treat various diseases. Ultrasound technology allows quick visualization of the kidneys and related structures from outside the body. Ultrasound may also be used to assess blood flow to the kidneys. The specific information can also be obtained to evaluate the diseases. Histogram equalization is one of the important steps in image enhancement technique for KUI. There are several methods of image enhancement and each of them is needed for a different type of analysis. In this paper study and comparison of different techniques like histogram equalization, local histogram equalization (LHE), adaptive histogram equalization (AHE) and contrast limited adaptive histogram equalization (CLAHE) using different objective quality measures for kidney ultrasound image enhancement.
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Cheruku Sandesh Kumar, Ratnadeep Roy, Archek Praveen Kumar, Ashwani Kumar Yadav. Histogram Equalization for Image Enhancement Using Kidney Ultrasound Images. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(2): 20–26p.
Pratik Vinayak Oak, Kamathe RS. Contrast Enhancement of Images Using Histogram Based Techniques. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering. 2013.
Arici T, Dikbas S, Altunbasak Y. A Histogram Modification Framework and its Application for Image Contrast Enhancement. IEEE Trans. Image Process. Sep 2009; 18(9): 1921–1935p.
Celik T, Tjahjadi T. Automatic Image Equalization and Contrast Enhancement Using Gaussian Mixture Modeling. IEEE Trans. Image Process. Jan 2012; 21(1): 145–156p.
Abdullah-Al-Wadud M, Kabir Md. H, Dewan MAA, et al. A Dynamic Histogram Equalization for Image Contrast Enhancement. IEEE Trans. Consumer Electron. May 2007; 53(2): 593–600p.
Gonzalez R, Woods R. Digital Image Processing using Matlab Reading, MA, USA: Addison-Wesley. 1993.
Stamm M, Liu KJR. Blind Forensics of Contrast Image Enhancement in Digital Images. In Proc. IEEE Int. Conf. Image Process. San Diego, CA. Oct 2008; 3112–3115p.
Nikolova M, Steidl G. Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement. IEEE Trans. Image Process. Sep 2014; 23(9): 4087–4100p.
Caselles V, Lisani J-L, Morel J-M, et al. Brightness Preserving Local Histogram Modification. IEEE Trans. Image Process. Feb 1999; 8(2): 220–229p.
Sen D, Pal SK. Automatic Exact Histogram Specification for Contrast Image Enhancement and Visual System Based Quantitative Evaluation. IEEE Trans. Image Process. May 2011; 20(5): 1211–1220p.
Rajesh Kumar, Harish Sharma, Suman. Comparative Study of HE Schemes. International Journal of Research in Management, Science & Technology. 1(1).
Abdullah Al Wadud M, et al. Modern Histogram Equalization Method for Image Enhancement. International Journal of Science and Technology. 2013; 11(3): 706–712p.
Rajesh Garg, Bhawna Mittal, Sheetal Garg. Histogram Equalization Techniques for Image Enhancement. IJECT. Mar 2011; 2(1).
Rajamani V, Babu P, Jaiganesh S. A Review of Various Global Contrast Enhancement Techniques for Still Images Using Histogram Modification Framework. International Journal of Engineering Trends and Technology. 2013.
Alex Stark J. Adaptive Image Contrast Enhancement Using Generalizations of Histogram Equalization. IEEE Trans. Image Process. 2000; 9.
Elisabeta Antonia Haller. Adaptive Histogram Equalization in GIS. Mathematics and Computer Science Series. 2011; 38(1): 100–104p.
Annadurai S, Shanmugalakshmi R. Fundamentals of Digital Image Processing. Pearson Education. 2007.
Pradeep, Namratha M, Manu GV. Global and Localized Histogram Equalization of an Image. International Journal of Computational Engineering Research. 2012; 2.
Manpreet Kaur, Jasdeep Kaur, Jappreet Kaur. Survey of Contrast Enhancement Techniques Based on Histogram Equalization. International Journal of Advanced Computer Science and Applications. 2011; 2.
Nyamlkhagva Sengee, Heung Kook Choi. Brightness Preserving Weight Clustering Histogram Equalization. International Conference on Computer Design and Applications (ICCDA 2010).
Gorai A, Ghosh A. Gray-level Image Enhancement by Particle Swarm Optimization. Machine Intell. Unit, Indian Stat. Inst., India. Dec 2009; 72–79p.
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