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A lightweight adaptive multi-frequency image sharpening library.

Project description

Athor - Md Istiak Tanvir (eruddro@gmail.com) Asma Akter (asmaul9377@gmail.com)

Overview -

image-sharpner is a lightweight and efficient image enhancement library designed to improve edge clarity, restore fine textures, and enhance visual details through an adaptive multi-frequency sharpening technique. The package supports both grayscale and color images and works seamlessly with popular computer vision pipelines.

Key Features -

  1. Adaptive multi-frequency sharpening to enhance details without amplifying noise
  2. Preserves natural textures and avoids halo artifacts
  3. Works with underwater, low-light, and blurred images
  4. Fast, NumPy-based implementation compatible with OpenCV
  5. Easy integration into machine learning, deep learning, and image-processing workflows

Why Use This Package? Traditional sharpening filters often overshoot edges, create ringing artifacts, or boost noise in smooth regions.

Installation - ----pip install image-sharpner-----

Usage Example - -----from image_prep import image_sharpner---- #Insert Image path - -----sharp = image_sharpner('abc.jpg')----

Supported Image Types - jpg/png/jpeg

Compatibility - Python 3.7+ NumPy OpenCV

License - MIT License

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