> For the complete documentation index, see [llms.txt](https://docs.qolaba.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.qolaba.ai/image-generation/image-editing/background-removal.md).

# Background Removal

How to use Background Removal in Qolaba — how it works, best input images for clean results, and common use cases.

Background Removal automatically detects the subject of an image and removes the background — producing a clean, isolated subject ready for use in design, marketing, and content workflows.

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#### What Background Removal Does

The tool analyzes the uploaded image, identifies the primary subject, and removes everything behind it. The output is a clean image with the subject isolated — typically exported with a transparent background ready for placement on any new background or design layout.

**Common use cases:**

* Product photography — isolate products for e-commerce listings and marketing materials
* Headshots and portraits — remove backgrounds for professional profile images or team pages
* Design compositing — extract subjects for use in posters, banners, and creative layouts
* Social media assets — create clean, versatile visuals for use across multiple backgrounds
* Marketing creatives — prepare subjects for placement on brand-consistent backgrounds

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#### How to Use Background Removal

* **Step 1 —** Open **Image Editing → Background Removal** from the workspace.
* **Step 2 —** Upload the image you want to process, or select one from your generation history.
* **Step 3 —** Review the credit cost displayed.
* **Step 4 —** Click **Generate**. The tool processes the image and returns the subject with the background removed.
* **Step 5 —** Download the output or use it as a reference input for a new generation.

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#### Tips for Clean Background Removal Results

1. **Use images with clear subject separation** The tool performs best when there is strong visual contrast between the subject and background. High-contrast images with a clearly defined subject edge produce the cleanest removal.
2. **Avoid complex or busy backgrounds when possible** Images with intricate backgrounds — dense foliage, patterned surfaces, or multiple overlapping elements — may produce less precise edges. Simpler backgrounds consistently yield cleaner results.
3. **Use high-quality, well-lit source images** Blurry, low-resolution, or poorly lit images make subject detection less accurate. A sharp, well-exposed source image produces a significantly cleaner output.
4. **Review edges after processing** Check the subject edges in the output before using it in a design. Fine details like hair, fur, or transparent elements may require additional refinement in a design tool if precision is critical.