IRIS.ANALYST

Per-Title, Per-Shot, and Content-Adaptive Encoding with IRIS.ANALYST

Not all video content is created equal, different scenes require different bitrates to deliver high-quality results. While we want to avoid wasting bandwidth, we also aim to preserve every detail. IRIS.ANALYST enables smarter encoding decisions by analyzing spatial and temporal complexity at the per-title and per-shot level.

Noise and grain are part of a video's spatial and temporal signal. As noted by Netflix, these factors alone can impact bitrate needs by up to 30%. At Wavelet Beam, we've confirmed this: leveraging IRIS.ANALYST can lead to a 30% reduction in bitrate, while maintaining or improving perceived visual quality.

IRIS.ANALYST Feature Set:

  • Automatic selection of video noise profiles
  • Scene and cut detection for per-shot encoding
  • Measurement of video resolution, no test target required
  • Quantified video noise levels using PSNR [dB]
  • Spatial and temporal complexity measurement
  • Contrast and brightness evaluation

The first video has audio: press play to hear the explanation.

The LA Downtown and Tiger clips above are zoomed and scaled from 9K to UHD (shot on 9x7).

Results and Insights

Measurements and findings from our work, summarized from Dirk Hildebrandt's posts and articles.

  1. Per-shot analysis in a single pass

    IRIS.ANALYST analyzes the spatial and temporal complexity of every shot, selects the optimal noise profile automatically and feeds a clean, metadata-rich signal into a single-pass encode, without convex hull or encoding loops.

    Read on LinkedIn

  2. Counting bad frames at UHD below 10 Mbit/s

    In a critical low-light Meridian scene at 9.6 Mbit/s, IRIS and IRIS.ANALYST reduced the frames below VMAF 93 from 25.73% to 13.29% and the frames below 40 dB PSNR from 51.62% to 10.15%.

    Read on LinkedIn

  3. Noise floor analysis: Sony VENICE 2

    Image information is part of the video noise floor. Even lossy compression ratios below 10:1 affect picture quality, so "visually lossless" is a misleading term. The less you compress, the less image information you lose.

    Read on LinkedIn

  4. Dead pixel detection

    Because the Wavelet Beam technology distinguishes between picture information and noise, dead pixels in cameras and film scanners can be discovered easily.

    Read on LinkedIn

  5. HPA Tech Retreat 2015: Image Analysis for Enhanced Quality

    Talk by Wavelet Beam's CTO at the Hollywood Post Alliance Tech Retreat: intelligent image analysis and dynamic denoising, combined with an adapted metadata workflow, enhance all distribution feeds independently of resolution and format.

    Read on LinkedIn

Frequently Asked Questions

What does IRIS.ANALYST measure?

Among others: horizontal video resolution without a test target, noise levels per color channel, spatial energy, brightness and contrast, per shot.

What is IRIS.ANALYST used for?

Its per-shot metadata drives per-shot encoding in a single pass. With IRIS.ANALYST, bitrate reductions of up to 30% are possible while maintaining or improving perceived quality.

Does IRIS.ANALYST need a test chart?

No. IRIS.ANALYST measures the effective video resolution, noise levels per color channel, spatial energy, brightness and contrast directly on the content.

Can IRIS.ANALYST detect defective pixels?

Yes. Because it distinguishes between picture information and noise, dead or hot pixels of cameras and film scanners stand out clearly.