Author - 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 -
- Adaptive multi-frequency sharpening to enhance details without amplifying noise
- Preserves natural textures and avoids halo artifacts
- Works with underwater, low-light, and blurred images
- Fast, NumPy-based implementation compatible with OpenCV
- 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 - ---import cv2---- ----from image_prep import image_sharpner----
----img = cv2.imread("input.jpg")--- -----sharp = image_sharpner(img)
Supported Image Types - jpg/png/jpeg
Compatibility - Python 3.7+ NumPy OpenCV
License - MIT License