Digital-Image-Processing

This repository contains Python implementations of various image processing techniques using OpenCV and NumPy.

Implemented Techniques

Image Negative – Inverts image colors.
Log & Power-Law Transformation – Enhances brightness and contrast.
Spatial Filtering – Applies smoothing and sharpening filters.
Image Enhancement – Arithmetic and logical operations on images.
Image Transformations – Fourier and other domain-based transformations.
Histogram Processing – Equalization and contrast adjustments.
Frequency Domain Processing – Image analysis in the frequency spectrum.
Color Image Processing – Manipulation of multi-channel images.
Image Segmentation – Object detection and edge-based segmentation.
Morphological Processing – Operations like erosion, dilation, and edge detection.
Image Registration – Aligning images for further processing.

Name		Name	Last commit message	Last commit date
Latest commit History 23 Commits
Images		Images
Color_Image_Processing.ipynb		Color_Image_Processing.ipynb
Frequency_Domain_Processing.ipynb		Frequency_Domain_Processing.ipynb
Hira_DIP_Record.pdf		Hira_DIP_Record.pdf
Image_Morphological_Processing.ipynb		Image_Morphological_Processing.ipynb
Image_Negative.ipynb		Image_Negative.ipynb
Image_Segmentation.ipynb		Image_Segmentation.ipynb
Log_Transformation.ipynb		Log_Transformation.ipynb
Power_Law_Transformation.ipynb		Power_Law_Transformation.ipynb
README.md		README.md
Spatial_Filtering.ipynb		Spatial_Filtering.ipynb
image_enhancement_arithmetic_logic_operations.py		image_enhancement_arithmetic_logic_operations.py
image_registration.py		image_registration.py
image_transform.py		image_transform.py
intensity_transformation_and_histogram_processing.py		intensity_transformation_and_histogram_processing.py