Enhancing Image Quality for Smart TV Camera on Large Screens

1. Context

This initiative focused on improving image quality for a smart TV camera, ensuring an optimal visual experience on large screens (50+ inches). Given the display size, key factors such as color accuracy, sharpness, exposure adaptation, and low-light performance were critical.

When I joined the project, there were opportunities to refine image processing through software-based enhancements to improve real-world performance before and after launch. The goal was to structure a plan that prioritized high-impact fixes while working within tight launch timelines.

2. Challenge

Key challenges included:

• Time constraints: The product was a few months from launch, so software optimizations had to be thoroughly tested without causing delays.
• Diverse use cases: Different applications (apps) had varying image quality requirements:
  • Interactive applications (apps): Required precise body and face tracking for responsiveness.
  • Video communication apps: Needed accurate color fidelity, clear facial details, and balanced exposure in different lighting conditions.
• Hardware limitations: While software adjustments could address most issues, certain hardware-level improvements were not feasible before launch, as the cameras were already in production.

3. Approach

A customer-centric, real-world testing approach was adopted, with a structured method to first identify areas for improvement before refining solutions:

• Understanding key improvement areas: Conducted in-depth analysis to pinpoint areas such as image noise, glare artifacts, and auto-focus inconsistencies across different brightness levels and light sources.
• Testing real-world scenarios: Evaluated video performance across flagship applications (apps) under varied home lighting conditions.
• Prioritizing high-impact enhancements: Implemented a phased approach: Phase 1: Focused on quick software fixes, improving color accuracy through white balance calibration and saturation adjustments, along with noise reduction in low-light conditions. Phase 2: Further refinements, targeting noise reduction, graininess improvement, sharpness, detail preservation, and exposure balance.
• Extensive post-launch testing: Conducted live testing sessions with internal teams and trial users to validate software iterations in real-world environments.

4. Role & Achievements

As a Senior Product Manager for video calling app experience, my primary role at the kickoff stage was to set the direction by first identifying key areas for optimization. In the early phase, I played a crucial role in recognizing image noise causing grainy picture quality, glare artifacts, and inconsistencies in auto-focus and auto-exposure under dynamic lighting as priority areas for enhancement.

• Identified and prioritized: Key camera performance improvement areas in collaboration with engineering, product, and testing teams.
• Conducted hands-on evaluations: Using multiple applications to capture real-world image quality challenges.
• Worked closely with engineering teams: To implement and validate progressive software improvements, ensuring measurable enhancements.
• Conducted in-depth image quality analysis: Evaluated video call performance to detect and categorize key visual distortions such as noise, glare, and unstable auto-focus behavior.
• Collaborated with engineering and testing teams: To refine detection methodologies and validate real-world impact across diverse user environments.
• Led prioritization efforts: Focused on mitigating image noise as the primary issue, aligning with direct customer feedback and optimizing software enhancements accordingly.

5. Results

• Phase 1 (Pre-launch):
  • Successfully implemented software optimizations, improving color accuracy and reducing noise in low-light conditions.
• Phase 2 (Post-launch):
  • Delivered targeted refinements, improving sharpness, exposure balance, and clarity.
  • User feedback confirmed noticeable improvements across various lighting conditions.
  • Exposure tuning helped reduce excessive brightness in well-lit scenarios.
• Future considerations:
  • Additional refinements, including automated framing enhancements, were planned for future updates, though I was not directly involved in that phase.

The improvements from both phases were well received and recognized by senior management as a critical enhancement to the smart TV camera experience.