How to Write High-Quality AI Image Prompts

Why “High Quality” Alone Rarely Works

Many beginners start with a prompt like:

“High quality portrait of a woman.”

This usually fails because the model does not know what kind of quality you want. Image quality is not a single switch. It is the result of multiple elements working together—texture, lighting, composition, and camera behavior.

A better strategy is to describe the components of quality in concrete terms:

• Surface detail (skin pores, fabric weave, hair strands)
• Lighting (soft key light, rim light, cinematic shadows)
• Optics (depth of field, focal length, bokeh)
• Focus (sharp eyes, controlled background blur)
• Cleanup constraints (avoid extra fingers, distortion, plastic skin)

The 5 Building Blocks of a Great Prompt

Use this simple structure in almost any model:

1. Subject: who/what is in the image
2. Scene: where they are, what is happening
3. Style: photographic, cinematic, illustration, concept art
4. Lighting + camera: how it is shot
5. Quality and constraints: the detail level and what to avoid

Example (portrait)

“Close-up portrait of a young adult, neutral expression, simple studio background, photorealistic, soft key light and subtle rim light, shallow depth of field, sharp focus on eyes, detailed skin texture, natural color grading.”

Portrait Quality: Skin, Eyes, Hair, and Fabric

If your portraits look waxy or artificial, you need to guide the model toward believable micro-detail.

Skin and facial detail keywords

• Skin texture: realistic skin texture, visible skin pores, fine skin detail
• Light behavior on skin: subsurface scattering (helps avoid flat plastic-looking skin)
• Natural imperfections: freckles, fine wrinkles, skin detail
• Eyes and gaze: sharp focus on eyes, highly detailed eyes, catchlights
• Hair and brows: individual hair strands, detailed eyebrows
• Clothing fibers: intricate fabric texture, detailed clothing fibers, woven fabric

Retouching (use carefully)

If you want a polished but still realistic look:

• natural makeup
• matte skin (reduces overly glossy skin)
• subtle skin retouching (avoid “perfect doll skin”)

Tip: If the model smooths skin too much, add:
avoid plastic skin, avoid overly smooth skin.

Lighting That Instantly Improves Results

Lighting is the fastest lever for better images. Use one lighting “recipe” per prompt so the model stays consistent.

Reliable lighting phrases

• soft natural light
• cinematic lighting
• volumetric lighting (visible light beams in mist or haze)
• rim lighting (a light edge around the subject)
• dramatic shadows (adds depth and contrast)
• golden hour / sunset glow (warm, flattering light)

Example lighting line for portraits

“Soft key light, gentle rim light, subtle shadows, cinematic color grading.”

Camera and Lens Words That Add Realism

Camera terms help the model “simulate” depth, perspective, and focus.

Useful camera keywords

• photorealistic, raw photo
• shallow depth of field, bokeh
• sharp focus, tack sharp eyes

Lens and settings (optional, but effective)

• shot on 85mm lens (classic portrait compression)
• shot on 35mm lens (more environmental context)
• f/1.8 or f/2.0 (strong background blur)

Tip: Do not overload your prompt with too many camera brands or models. One lens choice and one aperture is enough for most use cases.

Negative Prompts (When and How to Use Them)

Negative prompts tell the model what to avoid. They are especially common in Stable Diffusion workflows.

Common negative prompt items (portrait-friendly)

• bad anatomy, deformed
• extra fingers, extra limbs
• blurry, low resolution
• plastic skin
• asymmetrical face, distorted eyes

Note: Some tools do not support negative prompts directly. In those cases, write constraints in plain English, for example:
“Do not add extra fingers. Keep hands natural.”

Photo Restoration: A Step-by-Step Workflow

Restoring old or low-resolution portraits is easiest when you approach it as a pipeline:

1. Denoise and deblur (remove noise, reduce motion blur)
2. Repair damage (scratches, dust, compression artifacts)
3. Face refinement (recover eyes, facial symmetry, natural texture)
4. Upscale (increase resolution after the main cleanup is correct)
5. Color correction and finishing (natural skin tones, balanced contrast)

What often goes wrong in restoration

• The model “re-invents” the face instead of restoring it
• Over-sharpening creates halos or crunchy textures
• Skin becomes overly smooth, or pores become unnaturally large
• Colors become unrealistic (orange skin, neon clothing)

How to keep the person recognizable

Include constraints like:

• “Preserve identity and facial structure.”
• “Do not change age, facial features, or expression.”
• “Keep the same hairstyle and clothing.”

If your tool supports it, use image-to-image or reference image features rather than generating from scratch.

Copy-and-Paste Prompt Templates

Use these templates as starting points. Replace bracketed text with your details.

Template A: Photorealistic portrait (general)

Close-up portrait of [subject description], [simple background or environment],
photorealistic, detailed skin texture, visible skin pores, natural imperfections,
soft key light, subtle rim light, cinematic color grading,
shallow depth of field, bokeh, sharp focus on eyes, high detail hair strands,
realistic fabric texture, clean composition

Template B: Cinematic portrait (more dramatic)

Portrait of [subject], cinematic composition, dramatic shadows, rim lighting,
volumetric lighting, moody atmosphere, realistic skin texture, detailed eyes,
shot on 85mm lens, f/1.8, shallow depth of field, sharp focus, film-like color grading

Template C: Art-style, high detail (stylized but dense)

[subject and scene], intricate details, highly detailed materials and textures,
epic composition, dramatic lighting, volumetric effects, sharp edges,
concept art style, rich atmosphere, high detail environment

Template D: Old photo restoration (colorize + repair)

Restore this old photo with natural results.
Remove dust, scratches, and film grain; reduce blur; fix compression artifacts.
Preserve identity and facial structure; keep the same expression.
Colorize with natural skin tones and realistic hair color.
Enhance eyes and hair detail without making skin look plastic.
Clean, professional photo restoration finish; balanced contrast and color.

Stable Diffusion-style: Positive + Negative prompts

Positive prompt example

photorealistic portrait, detailed skin texture, visible skin pores, subsurface scattering,
soft natural light, shallow depth of field, bokeh, sharp focus on eyes, 85mm lens, f/1.8

Negative prompt example

bad anatomy, deformed, extra fingers, extra limbs, blurry, low resolution,
plastic skin, distorted eyes, asymmetrical face, overexposed, oversharpened

Common Mistakes and Quick Fixes

1) “Everything is in the prompt, but it still looks wrong”

Fix: Reduce conflict. Choose one style direction and one lighting setup. Too many styles fight each other.

2) Faces look “too perfect” or “too smooth”

Fix: Add: natural skin detail, fine texture, and explicitly avoid “plastic skin.”

3) Hands are distorted

Fix: Use negative terms (if available) like extra fingers, and keep hands less prominent:
“Hands relaxed, partially out of frame.”

4) The image is sharp but feels flat

Fix: Add depth cues: rim lighting, dramatic shadows, depth of field, and a clear subject-background separation.

5) Restoration changes the person’s identity

Fix: Add stronger constraints: “preserve identity,” “do not change facial structure,” and use a reference image workflow where possible.

FAQ

Which model is best for beginners?

Any mainstream tool can work if you write structured prompts. If your tool supports negative prompts and image-to-image, restoration workflows become easier.

Should I always use “8K” or “masterpiece” keywords?

Not always. They can help in some systems, but they can also add noise or push the model toward unrealistic textures. Start with concrete descriptions (lighting, texture, focus) and add broad quality tags only if needed.

Can AI restore very blurry photos perfectly?

If key facial details are missing, the model must “guess.” The goal becomes a plausible reconstruction, not a guaranteed accurate recovery. For important restoration tasks, always keep the original and compare results carefully.

What about privacy?

Avoid uploading sensitive or personal images to tools you do not trust. Use local workflows if privacy is critical.

Summary

Improving AI image results is less about writing “high quality” and more about describing how quality appears:

• Add texture (skin, hair, fabric) to avoid plastic surfaces
• Define lighting (soft key light, rim light, cinematic shadows) for depth
• Use camera behavior (depth of field, bokeh, lens choice) for realism
• Apply constraints (negative prompts or plain-English rules) to reduce artifacts
• For restoration, follow a pipeline: clean → refine → upscale → finish