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Digital Image Processing the complete guide in 2020

  • Course level: Beginner

Description

Digital Image Processing.

Interested to know about the field of Image Processing? Then this course is for you!

This course has been designed so that we can share our knowledge and help you learn complex theories, techniques, and concepts in a simple way.

We will walk you into the World of Image Processing. With every tutorial, you will develop new skills and improve your understanding of this field. While preparing this course special care is taken that the concepts are presented in a fun and exciting way but at the same time, we dive deep into Image Processing.

Digital Image Processing

Here is a list of few of the topics we will be learning:

  1. Image and Pixels
  2. Image Processing model / fundamental steps
  3. Color Models
  4. Image enhancement
  5. Point Processing Operations
  6. Neighborhood Processing
  7. Histograms
  8. Frequency domain
  9. Transformations
  10. Point, line and Edge detection
  11. Local and global processing
  12. Real-World Applications

Who this Digital Image Processing course is for:

  1. Students who want to study the domain in less than 2 hrs.
  2. Students, Researchers, and faculty who are interested in learning Image Processing and its techniques.
  3. Technologists who are curious about how the images are handled and worked upon.
  4. People who want to brush up on their basics.

What Will I Learn?

  • Understand the fundamentals of Image Processing, Image Enhancement, Image Segmentation.
  • To understand the different techniques and algorithms of image enhancement.
  • To apply different transformations on digital images.
  • To understand how these different domains are distinct and how they collaborate as well.
  • To apply these concepts in real life applications.

Topics for this course

68 Lessons

Digital Image Processing Lecture Series

Lecture 0 – Digital Image Processing00:00:00
Lecture 1 – Digital Image Processing – Introduction of DIP00:00:00
Lecture 2 – Digital Image Processing – Nature of Image Processing & Applications (AKTU)00:00:00
Lecture 3 – Digital Image Processing – Digital Image Representation & Operations (AKTU)00:00:00
Lecture 4 – Digital Image Processing – Elements of DIP & Steps in DIP (AKTU)00:00:00
Lecture 5A -Digital Image Processing – Types of Images (AKTU)00:00:00
Lecture 5B – Digital Image Processing – Image Storage and File Format (AKTU)00:00:00
Lecture 6A – Digital Image Processing – Digital Imaging Systems (AKTU)00:00:00
Lecture 6B – Digital Image Processing-Physical Aspects of Image Acquisition (AKTU)00:00:00
Lecture 7 – DIP – Biological Aspects of Image Acquisition (AKTU)00:00:00
Lecture 8 – DIP – Sampling and Quantization (AKTU)00:00:00
Lecture 9A – DIP- Digital Halftone Process (AKTU)00:00:00
Lecture 9B – DIP – Numericals on Dithering Algorithms (AKTU)00:00:00
Lecture 10 – Digital Image Processing – Need for Image Transforms (AKTU)00:00:00
Lecture 11A – Digital Image Processing – Properties of Fourier Transform (AKTU)00:00:00
Lecture 11B – Digital Image Processing – DCT & DST (AKTU)00:00:00
Lecture 12A – Digital Image Processing – Walsh Transform (AKTU)00:00:00
Lecture 12B – Digital Image Processing – Hadamard Transform (AKTU)00:00:00
Lecture 13A – Digital Image Processing – Haar Transform (AKTU)00:00:00
Lecture 13B – Digital Image Processing – Slant Transform (AKTU)00:00:00
Lecture 14 – Digital Image Processing – SVD & KL Transforms (AKTU)00:00:00
Lecture 15 – Digital Image Processing – Numericals on Image Transforms (AKTU)00:00:00
Lecture 16 – Digital Image Processing – Image Quality & Need for Image Enhancement (AKTU)00:00:00
Lecture 17 – Digital Image Processing – Image Enhancement in Spatial Domain (Part 1) (AKTU)00:00:00
Lecture 18 – Digital Image Processing – Image Enhancement in Spatial Domain (Part 2) (AKTU)00:00:00
Lecture 19 – Digital Image Processing – Numericals on Image Enhancement in Spatial Domain00:00:00
Lecture 20 – Digital Image Processing – Histogram based Techniques (Part-1) (AKTU)00:00:00
Lecture 21A – Digital Image Processing – Histogram Equalization (AKTU)00:00:00
Lecture 21B – Digital Image Processing – Histogram Specification (AKTU)00:00:00
Lecture 22A – Digital Image Processing – Spatial Filtering Concepts (AKTU)00:00:00
Lecture 22B – Digital Image Processing – Image Smoothing Spatial Filters (AKTU)00:00:00
Lecture 23 – Digital Image Processing – Image Sharpening Spatial Filters(AKTU)00:00:00
Lecture 24 – Digital Image Processing – Image Smoothing in Frequency Domain Filtering (AKTU)00:00:00
Lecture 25 – Digital Image Processing – Image Sharpening in Frequency Domain Filtering00:00:00
Lecture 26 – Digital Image Processing – Homomorphic Filtering (AKTU)00:00:00
Lecture 27 A – Digital Image Processing – Introduction to Degradation (AKTU)00:00:00
Lecture 27 B – Digital Image Processing – Image Degradation (Restoration) Model (AKTU)00:00:00
Lecture 28 – Digital Image Processing – Noise Modelling (AKTU)00:00:00
Lecture 29 – Digital Image Processing – Estimation of Degradation Function (AKTU)00:00:00
Lecture 30 – Digital Image Processing – Image Restoration in presence of Noise Only (AKTU)00:00:00
Lecture 31 – Digital Image Processing – Periodic Noise, Band-Pass & Band-Reject Filtering (AKTU)00:00:00
Lecture 32 – Digital Image Processing – Image Restoration Techniques00:00:00
Lecture 33 – Digital Image Processing – Inverse Filters00:00:00
Lecture 34 – Digital Image Processing – Wiener Filters00:00:00
Lecture 35 – Digital Image Processing – Constrained Least Square Filters00:00:00
Lecture 36 – Digital Image Processing- Image Compression Model00:00:00
Lecture 37 – Digital Image Processing – Compression Measures00:00:00
Lecture 38 – Digital Image Processing – Compression Algorithm and Its Types00:00:00
Lecture 39 – Digital Image Processing – Types of Redundancy00:00:00
Lecture 40 – Digital Image Processing – Run-length Coding (RLC)00:00:00
Lecture 41 – Digital Image Processing – Huffman Coding00:00:00
Lecture 42 – Digital Image Processing – Shannon Fano Coding00:00:00
Lecture 43 – Digital Image Processing – Bit Plane Coding00:00:00
Lecture 44 – Digital Image Processing – Arithmetic Coding00:00:00
Lecture 45 – Digital Image Processing – Dictionary based Coding00:00:00
Lecture 46 – Digital Image Processing – Lossless Predictive Coding00:00:00
Lecture 47 – Digital Image Processing – Lossy Predictive Coding00:00:00
Lecture 48 – Digital Image Processing – Vector Quantization00:00:00
Lecture 49 – Digital Image Processing – Block Transform Coding00:00:00
Lecture 50 – Digital Image Processing – Introduction to Image Segmentation00:00:00
Lecture 51 – Digital Image Processing – Detection of Discontinuities00:00:00
Lecture 52 – Digital Image Processing – First Order Edge Detection Operators in Image Segmentation00:00:00
Lecture 53 – Digital Image Processing – Second Order Derivative Filters in Image Segmentation00:00:00
Lecture 54 – Digital Image Processing – Hough Transform and Shape Detection00:00:00
Lecture 55 – Digital Image Processing – Corner Detection in Image Segmentation00:00:00
Lecture 57 – Digital Image Processing – Region Growing Algorithm00:00:00
Lecture 58 – Digital Image Processing – Split and Merge Algorithm00:00:00
Lecture 56 – Digital Image Processing – Principle of Thresholding00:00:00
Digital Image Processing
Free

Enrolment validity: Lifetime

Requirements

  • Basic knowledge of matrix multiplication and basic arithmetic and logical operations.