IMAGE PROCESSING USING MATLAB TRAINING COURSE MODULE

As raw data from imaging sensors from satellite platform contains deficiencies. To get over such flaws and to get originality of information, it has to undergo various phases of processing. The three general phases that all types of data have to undergo while using digital technique are Pre-processing, enhancement and display, information extraction.  

Module 1: Working with Images

Objective: Understand different image types available in IMAGE PROCESSING, and how they can be read into IMAGE PROCESSING.

1. Image types
2. Supported IMAGE PROCESSING data types for representing images
3. Binary Images
4. Grayscale images
5. Index Images
6. RGB images
7. Importing and exporting images in IMAGE PROCESSING
8. Finding image pixel values
9. Calculating image statistics
10. Converting image formats

 

Module 2: Image Enhancement Techniques:

 

Objective: Enhance image characteristics by adjusting the Image intensity and isolating a region of interest,

1. Adjusting image intensity
2. Histogram stretching
3. Histogram equalization
4. Using arithmetic functions to enhance images
5. Correcting lens distortion

 

 

Module 3: Filtering Images

Objective: Understand how block processing works: implement spatial-domain and frequency-domain filters and use filtering techniques to reduce the effects of unwanted distortions.

1. Defining filtering
2. Filtering process
3. Performing filtering
4. Filtering applications: smoothing, edge detection, and sharpening
5. Region-of-interest processing
6. Specific applications of filtering

 

 

Module 4: Feature Extraction and Segmentation

Objective: Extract image features and measurements using different segmentation methodologies.

1. Isolating image features using thresholding
2. Performing morphological segmentation
3. Creation of structuring elements
4. Erosion and dilation
5. Measurement of region properties
6. Reconstructing images and object
7. Segmenting images based on texture