image-sharpner 0.1.8

A lightweight adaptive multi-frequency image sharpening library.

Author - Md Istiak Tanvir ([e-mail]) Asma Akter ([e-mail])

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/webmp

Compatibility - Python 3.7+ NumPy OpenCV

License - MIT License