Project 1 (Image Processing)

Image Enhancement using Image Processing Techniques

Explanation:

In this project activity, you will apply various image processing techniques to enhance the quality and appearance of digital images. Image processing plays a crucial role in computer vision, enabling us to improve the visual perception of images and extract useful information. By understanding the fundamental concepts covered in the lessons “Introduction to Computer Vision” and “Image Processing,” you will be able to implement basic image enhancement algorithms and gain hands-on experience in working with digital images.

Steps:

1. Select an Image: Choose a digital image that you would like to enhance. You can use your own photograph or find a high-resolution image online. Ensure that the image represents a real-world scenario with visible details and features.

2. Load the Image: Use a programming language or an image processing software/library of your choice to load the selected image into your development environment. This will allow you to access and manipulate the pixel values of the image.

3. Convert to Grayscale (Optional): If your chosen image is in color, you may choose to convert it to grayscale for simplicity. This step is not mandatory but can be useful if you want to focus solely on grayscale image processing techniques.

4. Apply Contrast Enhancement: Implement a contrast enhancement algorithm, such as histogram equalization, to improve the overall contrast and dynamic range of the image. This will help bring out details and improve the visibility of objects in the image.

5. Implement Noise Reduction: Apply a noise reduction technique, such as Gaussian smoothing or median filtering, to reduce the presence of unwanted noise in the image. Noise reduction techniques help to improve image quality by removing or minimizing random variations in pixel values.

6. Edge Detection: Implement an edge detection algorithm, such as the Canny edge detector or Sobel operator, to identify and highlight the edges of objects in the image. Edge detection is useful for feature extraction and can enhance the perception of object boundaries.

7. Save and Compare: Save the enhanced image after applying the image processing techniques. Compare the original image with the enhanced version to visually evaluate the improvements achieved through the image processing steps.

By completing this project activity, you will have gained practical experience in applying image processing techniques to enhance digital images. This project serves as a foundation for further exploration into more advanced image processing methods and their applications in computer vision tasks.