Image Processing Library

Overview

This project is a basic Image Processing Library that focuses on handling grayscale images. Grayscale images are represented as 2D arrays of pixels, where each pixel has an intensity value ranging from 0 to 255. The value 0 represents black, 255 represents white, and values in between represent various shades of gray. The library includes several classes to manage image operations and associated geometric entities.

Features

Image Class

• Purpose: Represents a grayscale image as a 2D array of pixels.
• Pixel Values: Range from 0 (black) to 255 (white).
• Supported Operations:
  • Image Manipulation: Functions to load, save, and modify images.
  • Transformation: Apply operations such as rotation, scaling, and translation.

Size Class

• Attributes:
  • width (unsigned int): The width of the object.
  • height (unsigned int): The height of the object.
• Functions:
  • Constructors: Default and parameterized constructors.
  • Getters and Setters: Access and modify width and height.
  • Comparison Operators: Overload ==, <, <=, >, >= based on area.

Point Class

• Attributes:
  • x (int): X-coordinate of the point.
  • y (int): Y-coordinate of the point.
• Functions:
  • Constructors: Default (initializes to (0,0)) and parameterized constructors.
  • Getters and Setters: Access and modify x and y coordinates.

Rectangle Class

• Attributes:
  • x (int): X-coordinate of the top-left corner.
  • y (int): Y-coordinate of the top-left corner.
  • width (unsigned int): Width of the rectangle.
  • height (unsigned int): Height of the rectangle.
• Functions:
  • Constructors: Default and parameterized constructors.
  • Getters and Setters: Access and modify rectangle attributes.
  • Operators:
    • Addition/Subtraction with Point: Translate the rectangle.
    • Intersection (&): Compute the intersection of two rectangles.
    • Union (|): Compute the union of two rectangles.

Implementation Details

• Memory Management: Ensure proper handling of dynamic memory through the implementation of the Rule of Three (Destructor, Copy Constructor, and Assignment Operator).

• Error Handling: Robust error checking to handle scenarios such as out-of-bounds pixel access or invalid dimensions.

Testing

• Unit Tests: Comprehensive tests for each class and operation to ensure correctness, including:

  • Boundary checks for pixel values.
  • Validations for geometric transformations.
  • Memory management tests for potential leaks.

• Sample Use Cases: Examples demonstrating image loading, transformations, and geometric operations on images.