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Video Workflow: Understanding Video Quality Beyond Specs

You will edit any video for the story. One core question defines everything:

What is the quality of a video?

The quality that we sell or talk about often defines presentation, not the story. Cameras, codecs, picture profiles, LOG, or RAW do not automatically create a good video. They only provide options and flexibility in how the story is presented.

Key questions every creator must think about:

  • Will you colour correct?

  • Will you shoot LOG for great stories and efficient workflows?

  • Will you shoot RAW?

Each of these choices directly affects your workflow, file sizes, time investment, and creative freedom.

What Is a Camera?

A camera is a data-capturing device. It records light hitting the sensor and converts it into digital information. Unlike human vision, a camera does not understand context, emotion, or story—it only records measurable data. How this data is processed, compressed, and presented defines the final image or video we see.

Basic Complications of Working With a Camera

The camera and the human eye see the world very differently. However, our goal is always to produce images that feel like how humans saw the scene.

Loosely speaking, the relationship between the change in brightness of a scene and how we perceive it is very different from how a camera records it.

With a digital camera:

  • When twice the number of photons hit the sensor, it receives twice the signal.

  • Humans, however, perceive twice the light as being only a fraction brighter.

  • We are far more sensitive to changes in dark tones than to similar changes in bright tones.

This fundamental difference is the reason behind gamma curves, LOG profiles, and dynamic range management.

How Cameras See Colour

Cameras do not truly “see” colours. They approximate colours using mathematical models.

  • The approximation methods differ across camera brands.

  • Each manufacturer applies its own color science.

This is why footage from different brands looks different, even under the same lighting conditions.

(Refer to our detailed video on How Cameras See Colour for deeper understanding.)

Sampling, Compression, and Why Data Is Limited

Most of the time, the data that a camera captures is not complete data—it is sampled data.

This is done to:

  • Keep file sizes manageable

  • Make the process of scene reproduction economically viable

Over time, camera manufacturers have developed their own compression methods, most of which are based on universal logic. Depending on:

  • Required quality

  • Workflow needs

  • Storage and processing limitations

A compression method is chosen at the time of shooting.

Three Simplified Approaches to Video Shooting

At a very simplified level, there are three approaches a creator can take:

Choice 1: Premix Set – Straight Out of Camera

Choose a premix set and deliver footage directly from the camera.

Choice 2: Premix Set + Color Grade

Choose a premix set and color grade to taste.

Choice 3: Shoot RAW + Full Color Grade

Shoot RAW and color grade to match the story line or narrative.

These premix settings are popularly called Picture Profiles.

Picture Profiles: Making Tech Relatable

Picture profiles are the core of a camera’s color science. They are a logical system that practitioners use to stay consistent with a particular brand.

They are premix solutions that lead to predictable and acceptable results, such as cinematic looks like Cinetone.

Picture profiles process video signals before compression by:

  • Changing the gamma curve

  • Correcting colours before image quality is damaged by compression

Picture Profiles Are a Combination of:

  • Color Space (Color Gamut)

  • Non-linear data conversion (Gamma Curves)

  • Image edge and sharpness parameters

Examples of Picture Profiles:

  • S-Log 1, 2, 3

  • Cinelike

  • HLG3

  • Cine4

Gamma Curves Explained Simply

Gamma defines how smoothly black transitions to white on a digital display. It is often associated with numbers like 2.2 or 2.4, representing the curve’s shape.

Practical Importance of Gamma:

  • Helps distinguish grays between highlights and shadows

  • The gap between highlight and shadow is called contrast

  • The transition quality is called tonal quality

  • LOG is one form of gamma curve

Gamma curves compensate for:

  • Low bit depth

  • Limited dynamic range

They give more usable information in the midtones, where human vision is most sensitive.

What Is Important and Unacceptable

If a gamma curve is not smooth:

  • Transitions from black to white are uneven

  • Grays become harder to distinguish

  • Color and contrast suffer

This negatively impacts image quality and viewing experience.

Dynamic Range and Contrast

Dynamic range (also called contrast) is the difference between the darkest and brightest areas of a scene.

The Concept of Middle Grey:

Middle grey is based on surface reflectance. When light hits a surface and 50% is reflected, it is considered middle grey.

What Does a LOG Shoot Do?

As stated earlier, humans are more sensitive to information around middle grey.

In high-contrast scenes:

  • LOG shifts the middle grey to the right

  • Captures more information in darker areas

The primary purpose of LOG shooting is to preserve shadow details.

How LOG Works:

  • Redistributes light evenly

  • Maximizes midtone information

  • Middle grey typically sits between 32–38%

Shooting RAW: Maximum Data Capture

When you shoot RAW:

  • You get very large files

  • Files are often proprietary

To address this, Adobe introduced DNG (Digital Negative)—a universal RAW format.

Common RAW Formats:

  • R3D

  • ARW

  • CR3

  • DNG (Universal, open standard with wider support)

RAW workflow remains consistent:

  1. Capture

  2. Import

  3. Process in software

  4. Export to universal formats (JPG, video formats)

RAW shooting allows you to capture all available data the camera sees.

How This Translates to You

Before shooting video, you must define:

  • File size you can handle

  • Time available for delivery

  • End-use device for the video

Camera manufacturers now offer smart technologies to:

  • Simplify workflows

  • Keep the story in focus

Artificial Intelligence can be effectively combined with video to create stronger impact.

The Single Most Important Element After Story

Correct exposure of the footage is the single most important technical aspect.

Cameras with monitoring tools:

  • Help judge exposure accurately

  • Allow correction at the time of shooting

This ensures your footage remains usable, flexible, and story-driven.

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