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Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Got a conceptual compression question at Google that sounds deceptively simple but has a lot of moving parts if you actually think it through.

Questions Asked (1)

Q1

Why can a video file be compressed to a much smaller relative size compared to a still image?

Technical Trade-offsSystem Design
Author's notes

I started talking about codecs and then kind of wandered into bitrate territory before remembering the actual key point: temporal redundancy.

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AI HintsAI Generated

Suggested Approach

Start by explaining the fundamental difference in data redundancy: a still image is a single frame with limited spatial redundancy, while a video consists of many frames with high temporal redundancy. Then discuss how video codecs exploit both spatial and temporal redundancy, often achieving much higher compression ratios than image codecs. Finally, mention the trade-offs in complexity and quality.

Pro tip: Emphasize that video compression leverages inter-frame prediction (motion compensation) which is not available for still images, and that this is a key reason for the size difference. Also, note that the perceived quality can be maintained because human vision is less sensitive to certain temporal artifacts.

1. Define compression and redundancy

Explain that compression reduces file size by eliminating redundancy. Still images have only spatial redundancy, while videos have both spatial and temporal redundancy.

2. Explain spatial redundancy in images

Describe how image compression (e.g., JPEG) exploits spatial redundancy within a single frame, but is limited by the need to preserve details in that one frame.

3. Introduce temporal redundancy in video

Explain that consecutive video frames are often very similar, so video codecs can encode only the differences between frames (inter-frame prediction), drastically reducing data.

4. Discuss motion compensation and codec techniques

Mention techniques like motion estimation/compensation, keyframes (I-frames), and predictive frames (P/B-frames) that allow video to achieve much higher compression ratios.

5. Acknowledge trade-offs and limitations

Note that video compression is more complex, computationally intensive, and may introduce artifacts, but the high temporal redundancy makes the size reduction worthwhile.

Key Points to Mention

  • Spatial redundancy vs. temporal redundancy
  • Inter-frame prediction and motion compensation
  • Keyframes (I-frames) and delta frames (P/B-frames)
  • Human visual perception and acceptable quality trade-offs
  • Compression ratios: typical image compression (e.g., 10:1) vs. video compression (e.g., 100:1 or more)
  • Computational complexity and codec standards (e.g., H.264, HEVC)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.