Histogram Equalization: Enhancing Image Contrast for Enhanced Visual Perception

· Computer Vision ຫົວທີ 7 · One Billion Knowledgeable · AI ບັນຍາຍໂດຍ Maxwell (ຈາກ Google)
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What is Histogram Equalization


Histogram equalization is a method in image processing of contrast adjustment using the image's histogram.


How you will benefit


(I) Insights, and validations about the following topics:


Chapter 1: Histogram Equalization


Chapter 2: Cumulative Distribution Function


Chapter 3: Histogram


Chapter 4: Random Variable


Chapter 5: Order Statistic


Chapter 6: HSL and HSV


Chapter 7: Color Histogram


Chapter 8: Continuous Uniform Distribution


Chapter 9: Optical Resolution


Chapter 10: Empirical Distribution Function


(II) Answering the public top questions about histogram equalization.


(III) Real world examples for the usage of histogram equalization in many fields.


Who this book is for


Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Histogram Equalization.

ກ່ຽວກັບຜູ້ຂຽນ

Fouad Sabry is the former Regional Head of Business Development for Applications at HP. Fouad has received his B.Sc. of Computer Systems and Automatic Control in 1996, dual master’s degrees from University of Melbourne (UoM) in Australia, Master of Business Administration (MBA) in 2008, and Master of Management in Information Technology (MMIT) in 2010. Fouad has more than 30 years of experience in Information Technology and Telecommunications fields, working in local, regional, and international companies, such as Vodafone and IBM. Fouad joined HP in 2013 and helped develop the business in tens of markets. Currently, Fouad is an entrepreneur, author, futurist, and founder of One Billion Knowledge (1BK) Initiative.

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