Скачать или смотреть Digital Image Processing (DIP) – Unit 1: Chapter 2 | Sampling, Quantization & Pixel Relationships

This video covers Chapter 2 of Unit 1 in Digital Image Processing, focusing on the core foundational concepts required to understand how images are represented, analyzed, and processed digitally.

The lecture is designed to be clear, structured, and exam-oriented, making it suitable for both classroom learning and competitive exam preparation.

👨‍🏫 Instructor

Dr. Raushan Singh
PhD (IIT Ropar)

🔍 Topics Covered in This Video

Image Sampling and Quantization

Spatial Resolution and Intensity Resolution

Relationship between Pixels

Neighbourhood

Adjacency

Connectivity

Pixel Path

Region and Region Boundary

All concepts are explained using simple language, clear definitions, and intuitive examples, following standard textbooks such as Gonzalez & Woods.

🎯 Who Should Watch This Video?

This lecture is ideal for:

B.Tech / M.Tech / MCA students

Computer Science & Engineering students

AI, ML, and Computer Vision beginners

GATE and University exam aspirants

Anyone learning Digital Image Processing from fundamentals

🚀 Why This Chapter Is Important

Understanding sampling, quantization, and pixel relationships is essential because these concepts form the mathematical and logical foundation of:

Image enhancement

Image segmentation

Object detection

Computer vision systems

Machine vision applications

A strong grasp of this chapter is critical for advanced topics in Image Processing, AI, Robotics, and Computer Vision.

📚 Course Playlist

Digital Image Processing – Full Course (Unit-wise, Exam-Oriented)
(Playlist link)

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