Image-Sharpness-Map-Generator

The Image Sharpness Map Generator analyzes the clarity of an image by computing pixel-level and region-level sharpness. It visualizes how sharp or blurry different parts of an image are using the Laplacian operator, providing both heatmaps and numerical sharpness maps for detailed inspection. This tool can be used for image quality assessment.

What the Project Does

The script generates two types of visual outputs:

1. Sharpness Heatmap (Color Visualization)

• Converts the image to grayscale
• Applies Laplacian to measure sharpness
• Smooths the result and visualizes it using the JET colormap
• This gives a clear heatmap showing sharp (red/yellow) and blurry (blue) regions

2. Numeric Block-wise Sharpness Map

• Divides the image into small blocks
• Calculates sharpness value for each block
• Plots it as a heatmap with numbers
• Useful for analysis, ML preprocessing, or image quality evaluation

Run Commands

1. Clone the repository git clone https://github.com/Madhu-1106/Image-Sharpness-Map-Generator.git cd Sharpness-Map-Generator

2. Install dependencies

pip install -r requirements.txt

4. Launch the Jupyter Notebook

jupyter notebook sharpness_map.ipynb

6. Load input image

Place images inside:

Input Imgs/ (Notebook reads the image path directly.)

5. Execute all cells

Run → Run All

This generates: Sharpness heatmap Block-wise numerical sharpness map Output files stored in:

outputs/

--- Optional: If asked about running in Colab

Upload sharpness_map.ipynb Upload an image into /content/Input Imgs/ pip install -r requirements.txt Run all cells