image-sharpner 0.1.3

A lightweight adaptive multi-frequency image sharpening library.

Athor - 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 - ----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