- Understand the concept of image histograms and master the method of drawing them.
- Learn the principle of histogram equalization and apply it to image processing.
Convert a color image to a grayscale image, draw histograms (gray and equalized), and analyze the effect of histogram equalization.
- Image Selection: Choose a suitable color image and convert it to grayscale.
- Histogram Drawing: Implement histogram drawing and histogram equalization using any programming language.
- Completeness: Provide the complete project process, code, results, and analysis.
- main.py: Main script to execute experiments.
- experiment_executor.py: Class to run experiments and process images.
- image_processor.py: Class containing image processing functions.
- result_saver.py: Class for saving experiment results.
- data/: Directory containing input images.
- all_results/: Directory to store experiment results.
- Clone the repository:
git clone https://github.com/Hetawk/histogram-python.git - Navigate to the project directory:
cd histogram-python - Install dependencies:
pip install -r requirements.txt - Run the experiments:
python main.py
- Each experiment result will be saved in the
all_resultsdirectory. - Results include output images and histograms.
- Analyze the effect of histogram equalization on image contrast and brightness.
- Compare the original image, grayscale image, and equalized image.
