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A Python project demonstrating various image processing techniques, including noise reduction, filtering, geometric transformations, and feature extraction. The project applies median and smoothing filters, patch-based image restoration, histogram analysis, and edge detection to enhance and analyze images.

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YuvalBakirov/image-processing

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Image Processing Project

Overview

This project demonstrates a range of image processing techniques using Python and OpenCV (cv2). It consists of two main parts, each handling different images and applying various filters and algorithms.

Project Structure

Part 1: Super Mario Image Processing

- part-1-ex1.py - Applied two filters:

  • Median Filter: To reduce noise.
  • Basic Smoothing Filter: To blur the image slightly.

- part-1-ex3.py – Applied a patch-based algorithm to recover a missing portion of the image.

Part 2: Unique Image Processing and Analysis

- part-2.py – Performed the following:

  1. Grayscale Conversion: Analyzed the image in grayscale.
  2. RGB Histograms: Generated histograms for color distribution.
  3. Gradients and Intensity Analysis: Examined the image structure.
  4. Applied three image processing actions: Geometric Transformation (Rotation), Central Crop, and Sharpening Filter.

How to Run

To reproduce the project, clone the repository and run each of the Python files separately.

Technologies Used

  • Language: Python
  • Library: OpenCV (cv2)

About

A Python project demonstrating various image processing techniques, including noise reduction, filtering, geometric transformations, and feature extraction. The project applies median and smoothing filters, patch-based image restoration, histogram analysis, and edge detection to enhance and analyze images.

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