Spatial-domain processing (Histogram Processing) I

Описание: Understanding Image Histogram Processing and Enhancement Techniques

In this Tutorial, we dive deep into the concepts of image histogram processing and enhancement. We start by discussing the basics of image acquisition and the limitations of user input methods for image adjustment. The focus then shifts to augmented image processing techniques, particularly histogram processing. We explore how to count pixels and understand their distribution in an image, the concept of normalized histograms, and how these can indicate low and high contrast in images. Practical examples illustrate how to plot histograms, normalize them, and analyze probabilities of pixel intensities. We also delve into Continuous Distribution Functions (CDF) and their application in transforming images to achieve uniform histogram distributions. By the end, viewers will have a thorough understanding of how histogram processing can enhance image contrast and quality.

00:00 Introduction to Image Processing
00:26 Understanding Instagram Processing
00:38 Histogram and Pixel Intensity
01:33 Practical Examples of Histogram Processing
02:29 Normalization and Probability
03:46 Contrast and Histogram Equalization
07:30 PDF and CDF in Image Processing
08:58 Transformation Functions and Applications
11:47 Understanding the Equation
12:57 Transforming PDFs to Uniformity
13:18 Continuous Case and Signal Transformation
14:03 Deriving the PDF of S
18:02 Practical Examples and Applications
22:17 Histogram Matching Techniques