Image Enhancement Guide

Improve image quality for documentation, presentations, and social media.

When to Use

• Improving screenshot quality for blog posts
• Enhancing images for social media
• Preparing images for presentations
• Upscaling low-resolution images
• Sharpening blurry photos
• Cleaning up compressed images

Enhancement Workflow

1. Analyze – Check resolution, sharpness, artifacts
2. Enhance – Apply appropriate improvements
3. Optimize – Adjust for intended use case
4. Save – Preserve original, save enhanced version

Python Enhancement Script

from PIL import Image, ImageEnhance, ImageFilter

def enhance_image(input_path, output_path):
    img = Image.open(input_path)

    # Upscale if small
    if img.width < 1920:
        scale = 1920 / img.width
        new_size = (int(img.width * scale), int(img.height * scale))
        img = img.resize(new_size, Image.LANCZOS)

    # Sharpen
    img = img.filter(ImageFilter.SHARPEN)

    # Enhance contrast slightly
    enhancer = ImageEnhance.Contrast(img)
    img = enhancer.enhance(1.1)

    img.save(output_path, quality=95)
    return img.size

# Usage
enhance_image('screenshot.png', 'screenshot-enhanced.png')

ImageMagick Commands

# Sharpen image
convert input.png -sharpen 0x1 output.png

# Upscale 2x with good quality
convert input.png -resize 200% -filter Lanczos output.png

# Remove compression artifacts
convert input.jpg -enhance output.jpg

# Batch process folder
for f in *.png; do
    convert "$f" -sharpen 0x1 "enhanced-$f"
done

Optimization by Use Case

Social Media Sizes

Tips

• Always keep original files as backup
• PNG for screenshots (lossless)
• JPG for photos (smaller size)
• WebP for web (best compression)
• Batch process for multiple files

Required Tools

# Python
pip install Pillow

# ImageMagick
sudo apt-get install imagemagick

# For advanced upscaling
pip install opencv-python