Enhance Image Quality with AI

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Image & Video APIs

Last updated: Jun-26-2026

Cloudinary offers a range of ways to enhance your images, from fully automatic, AI-powered enhancement to targeted options for restoring, upscaling, and improving image quality. This page explains the differences between them and shows examples of each.

On this page:

Try the enhancement options
Auto enhance
Generative restore
Upscale
Enhance
Improve

Tip

If you're not sure which option to choose, try automatic enhancement, which intelligently decides which of the enhancement options to apply.

Transformation	Purpose	Key features	Main use cases	How it works
Auto enhance (e_auto_enhance)	Automatically enhances overall visual quality without you having to choose the enhancement option to apply.	✅ Analyzes image quality and automatically selects the right enhancement techniques to apply.	✅ Enhancing user-generated content. ✅ Improving the quality of low resolution images. ✅ Any images requiring a quality boost.	Uses AI to determine the best way to improve the image quality. If the image is already high quality, only minor adjustments are made. Otherwise, more aggressive enhancements are applied.
Generative restore (e_gen_restore)	Excels in revitalizing images affected by digital manipulation and compression.	✅ Compression Artifact Removal: Effectively eliminates JPEG blockiness and overshoot due to compression. ✅ Noise Reduction: Smoothens grainy images for a cleaner visual. ✅ Image Sharpening: Boosts clarity and detail in blurred images.	✅ Over-compressed images. ✅ User-generated content. ✅ Restoring vintage photos.	Utilizes generative AI to recover and refine lost image details.
Upscale (e_upscale)	Increases the resolution of an image using AI, with special attention to faces.	✅ Enhances clarity and detail while upscaling. ✅ Specialized face detection and enhancement. ✅ Preserves the natural look of faces.	✅ Improving the quality of low resolution images, especially those with human faces.	Analyzes the image, with additional logic applied to faces, to predict necessary pixels.
Enhance (e_enhance)	Enhances the overall appeal of images without altering content using AI.	✅ Improves exposure, color balance, and white balance. ✅ Enhances the general look of an image.	✅ Any images requiring a quality boost. ✅ User-generated content.	An AI model analyzes and applies various operators to enhance the image.
Improve (e_improve)	Automatically improves images by adjusting colors, contrast, and lighting.	✅ Enhances overall visual quality. ✅ Adjusts colors, contrast, and lighting.	✅ Enhancing user-generated content. ✅ Any images requiring a quality boost.	Applies an automatic enhancement filter to the image.

Try the enhancement options

Use this interactive demo to compare the different enhancement options on various sample images:

Select a sample image:

Choose enhancement option:

Comparison:

Original:

Enhanced:

Auto enhance

The auto_enhance effect uses AI to analyze image quality and automatically select the right enhancement techniques to apply. This eliminates the need to manually determine which enhancement options to use or tune their parameters.

Auto enhance is powered by intelligent generative AI models capable of addressing diverse image degradations that would otherwise require applying multiple different transformations, including:

Generative restore: Removes compression artifacts, reduces noise, and sharpens image details.
Upscale: Improves clarity and detail while scaling, with face detection and natural-looking face enhancements.
Enhance: Adjusts exposure, color, and white balance.
Improve: Enhances overall visual quality, including colors, contrast, and lighting.

How it works

Auto enhance intelligently adjusts the level of enhancement based on the input image quality:

High-quality images: Applies subtle, minimal adjustments.
Lower-quality images: Applies more advanced and noticeable enhancements.

Tip

If your images have color degradation, you can apply the enhance-colors_true parameter (e_auto_enhance:enhance-colors_true) for improved color enhancement.