AI Integrated Post Production Image Enhancement Workflow Guide

Post-production Image Enhancement Workflow

1. Initial Image Review

1.1. Gather Raw Footage

Collect all raw images and video files from the production phase.

1.2. Review Footage Quality

Assess the quality of the footage for color balance, exposure, and clarity.

2. Image Enhancement Preparation

2.1. Select AI Image Enhancement Tools

Identify suitable AI-driven tools for image enhancement, such as:

• Adobe Photoshop with Neural Filters: Utilize AI to enhance facial features and adjust lighting.
• Topaz Labs AI Clear: Remove noise and sharpen images using AI algorithms.
• DaVinci Resolve: Implement AI-driven color grading for consistent visual aesthetics.

2.2. Create Enhancement Guidelines

Establish criteria for enhancement based on project requirements and artistic vision.

3. AI-Driven Image Enhancement

3.1. Automated Noise Reduction

Use AI tools like Topaz Denoise AI to automatically reduce noise while preserving details.

3.2. Color Correction

Employ AI algorithms in DaVinci Resolve for automatic color correction and matching across scenes.

3.3. Image Upscaling

Utilize AI upscaling tools like Gigapixel AI to enhance resolution without losing quality.

4. Quality Assurance

4.1. Review Enhanced Images

Conduct a thorough review of enhanced images for consistency and quality.

4.2. Gather Feedback

Solicit feedback from the creative team to ensure alignment with the project vision.

5. Final Adjustments

5.1. Implement Revisions

Make necessary adjustments based on feedback received.

5.2. Final Quality Check

Perform a final quality check to ensure all enhancements meet the desired standards.

6. Export and Archive

6.1. Export Enhanced Images

Export the final enhanced images in required formats for distribution.

6.2. Archive Raw and Enhanced Files

Store both raw and enhanced files securely for future reference and potential re-editing.

7. Documentation and Reporting

7.1. Document Workflow Process

Record the workflow process, tools used, and outcomes for future projects.

7.2. Report on Performance Metrics

Analyze the efficiency of the AI tools employed and report on their impact on the enhancement process.