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DIP using MATLAB: Digital Image Processing for Beginners
Rating: 3.9 out of 5(225 ratings)
5,093 students

DIP using MATLAB: Digital Image Processing for Beginners

DIP (Digital Image Processing) using MATLAB course with certification for beginners by Industry experts at TELCOMA
Created byTELCOMA Global | Leading Since 2009 | 75,000+ Students
Last updated 9/2018
English
English [Auto],

What you'll learn

  • Perform Digital Image Processing using MATLAB
  • Learn M Function programming
  • Perform Intensity Transformations
  • Spatial Filtering
  • Frequency domain processing
  • Image Restoration and Reconstruction and Geometric transformations
  • Color image processing
  • Wavelets
  • Morphological image processing
  • Image segmentation

Course content

2 sections • 21 lectures • 4h 11m total length

  • Introduction7:20

    Learn the basics of digital image processing with MATLAB, defining images as 2d intensity functions and pixels, and using the image processing toolbox with MATLAB's desktop tools.

  • Fundamentals12:45

    Master the fundamentals of digital images in MATLAB, covering intensity, monochrome and RGB components, sampling and digitization, and reading, displaying, and indexing image pixels.

  • Introduction to M Function programming7:49

    Learn to create m-files and user defined functions in matlab, including function definitions, help text, inputs and outputs, and basic flow control with vectorization and preallocation.

  • Intensity Transformations11:15

    Explore intensity transformations in the spatial domain, including gamma correction, logarithmic and contrast stretching, and thresholding, with MATLAB toolbox functions for histogram processing and matching.

  • Spatial Filtering6:40

    Explore linear and nonlinear spatial filtering in MATLAB, using correlation or convolution, border handling, and predefined filters; learn median filtering to reduce salt-and-pepper noise.

  • Frequency domain processing11:05

    Explore frequency domain processing in MATLAB: compute the dft with fft2, pad and shift to center, apply low-pass and hypersphere high-frequency emphasis filters, then inverse transform.

  • Image Restoration and Reconstruction and Geometric transformations19:17

    Explore image restoration and reconstruction using degradation models, additive noise, and point spread function. Apply Fourier-based transfer functions, deconvolution, and filtering, then master geometric transformations and image registration for alignment.

  • Color Image Processing14:08

    Learn color image processing in matlab by combining red, green, and blue components. Work with indexed images and color maps; explore RGB, NTSC, and HSV spaces; apply smoothing and sharpening.

  • Wavelets6:28

    Explore the discrete wavelet transform for multi-resolution image analysis, using MATLAB's wavelet toolbox to decompose and reconstruct images with low-pass and high-pass filters across scales.

  • Image Compression6:55

    Explore image compression through encoder-decoder pipelines, measure with compression ratio, and analyze redundancies—coding, spatial and visual—entropy, quantization, and jpeg-style 8x8 block processing.

  • Morphological image processing10:19

    Explore morphological image processing using dilation and erosion on binary images, applying opening, closing, hit-or-miss, skeletonization, labeling connected components, and morphological reconstruction with structuring elements in MATLAB.

Requirements

  • System with Internet is required
  • Basic knowledge of MATLAB is required

Description

DIP (Digital image processing) is the use of computer algorithms to create, process, communicate and display digital images. As MATLAB is a high-performance language for technical computing with powerful commands and syntax, it is widely used for the DIP. The main purpose of Digital Image processing(DIP) is that the result is more fit than the initial image for a particular use.


Digital image processing methods provide a number of choices for improving the visual quality of images (e.g. image enhancement, images segmentation, images registration). Suitable selection of such methods is considerably controlled by the imaging modality, job at hand and viewing conditions.


Digital image processing algorithms can be used to: 

Transform signals from an image sensor into digital images 

Increase clarity, and eliminate noise and other artifacts 

Obtain the size, scale, or number of objects in a picture 

Prepare images for display or printing 

Compress images for transfer across a network


By the end of the course, you will be able to 

Perform Digital Image Processing using MATLAB

Learn M Function programming

Perform Intensity Transformations

Spatial Filtering

Frequency domain processing

Image Restoration and Reconstruction and Geometric transformations

Color image processing

Wavelets

Morphological image processing

Image segmentation


DIP using MATLAB Certification is included in the course which will be the proof of the new skills you own.


30 DAYS MONEY-BACK GUARANTEE

This  Course comes with Lifetime access so you can enjoy the updates to this course without paying anything extra.  You will also get a 30 Days Money Back Guarantee by Purchasing this course now. You are eligible for a full refund on this training within 30 days from purchase.

All this great value at the most genuine price! Taking action and buying this course now is better than doing nothing.

Who this course is for:

  • Anyone willing to learn Digital Image Processing using MATLAB

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