COLOR

  • Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in Nuke

    Answering the question that is often asked, “Do I need to use ACEScg to display an sRGB monitor in the end?” (Demonstration shown at an in-house seminar)
    Comparison of scanlineRender output with extreme color lights on color charts with sRGB/ACREScg in color – OCIO -working space in Nuke

    Download the Nuke script:

    Read more: Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in Nuke
  • Eye retina’s Bipolar Cells, Horizontal Cells, and Photoreceptors

    In the retina, photoreceptors, bipolar cells, and horizontal cells work together to process visual information before it reaches the brain. Here’s how each cell type contributes to vision:

     

    1. Photoreceptors

    • Types: There are two main types of photoreceptors: rods and cones.
      • Rods: Specialized for low-light and peripheral vision; they help us see in dim lighting and detect motion.
      • Cones: Specialized for color and detail; they function best in bright light and are concentrated in the central retina (the fovea), allowing for high-resolution vision.
    • Function: Photoreceptors convert light into electrical signals. When light hits the retina, photoreceptors undergo a chemical change, triggering an electrical response that initiates the visual process. Rods and cones detect different intensities and colors, providing the foundation for brightness and color perception.

     

    2. Bipolar Cells

    • Function: Bipolar cells act as intermediaries, connecting photoreceptors to ganglion cells, which send signals to the brain. They receive input from photoreceptors and relay it to the retinal ganglion cells.
    • On and Off Bipolar Cells: Some bipolar cells are ON cells, responding when light is detected (depolarizing in light), and others are OFF cells, responding in darkness (depolarizing in the absence of light). This division allows for more precise contrast detection and the ability to distinguish light from dark areas in the visual field.

     

    3. Horizontal Cells

    • Function: Horizontal cells connect photoreceptors to each other and create lateral interactions between them. They integrate signals from multiple photoreceptors, allowing them to adjust the sensitivity of neighboring photoreceptors in response to varying light conditions.
    • Lateral Inhibition: This process improves visual contrast and sharpness by making the borders between light and dark areas more distinct, enhancing our ability to perceive edges and fine detail.

     

    These three types of cells work together to help the retina preprocess visual information and perception, emphasizing contrast and adjusting for different lighting conditions before signals are sent to the brain for further processing and interpretation.

     

     

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    Read more: Eye retina’s Bipolar Cells, Horizontal Cells, and Photoreceptors
  • Scene Referred vs Display Referred color workflows

    Display Referred it is tied to the target hardware, as such it bakes color requirements into every type of media output request.

    Scene Referred uses a common unified wide gamut and targeting audience through CDL and DI libraries instead.
    So that color information stays untouched and only “transformed” as/when needed.

     

     

    Sources:
    – Victor Perez – Color Management Fundamentals & ACES Workflows in Nuke
    – https://z-fx.nl/ColorspACES.pdf
    – Wicus

     

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    Read more: Scene Referred vs Display Referred color workflows
  • Photography Basics : Spectral Sensitivity Estimation Without a Camera

    https://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/

     

    A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession.

     

    To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space.

     

    Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.

     

     

     

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    Read more: Photography Basics : Spectral Sensitivity Estimation Without a Camera
  • Tim Kang – calibrated white light values in sRGB color space

    https://www.linkedin.com/posts/timkang_colorimetry-cinematography-nerdalert-activity-7058330978007584769-9xln

     

    8bit sRGB encoded
    2000K 255 139 22
    2700K 255 172 89
    3000K 255 184 109
    3200K 255 190 122
    4000K 255 211 165
    4300K 255 219 178
    D50 255 235 205
    D55 255 243 224
    D5600 255 244 227
    D6000 255 249 240
    D65 255 255 255
    D10000 202 221 255
    D20000 166 196 255

    8bit Rec709 Gamma 2.4
    2000K 255 145 34
    2700K 255 177 97
    3000K 255 187 117
    3200K 255 193 129
    4000K 255 214 170
    4300K 255 221 182
    D50 255 236 208
    D55 255 243 226
    D5600 255 245 229
    D6000 255 250 241
    D65 255 255 255
    D10000 204 222 255
    D20000 170 199 255

    8bit Display P3 encoded
    2000K 255 154 63
    2700K 255 185 109
    3000K 255 195 127
    3200K 255 201 138
    4000K 255 219 176
    4300K 255 225 187
    D50 255 239 212
    D55 255 245 228
    D5600 255 246 231
    D6000 255 251 242
    D65 255 255 255
    D10000 208 223 255
    D20000 175 199 255

    10bit Rec2020 PQ (100 nits)
    2000K 520 435 273
    2700K 520 466 358
    3000K 520 475 384
    3200K 520 480 399
    4000K 520 495 446
    4300K 520 500 458
    D50 520 510 482
    D55 520 514 497
    D5600 520 514 500
    D6000 520 517 509
    D65 520 520 520
    D10000 479 489 520
    D20000 448 464 520

     

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    Read more: Tim Kang – calibrated white light values in sRGB color space
  • Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminance

    https://www.translatorscafe.com/unit-converter/en-US/illumination/1-11/

     

     

    The power output of a light source is measured using the unit of watts W. This is a direct measure to calculate how much power the light is going to drain from your socket and it is not relatable to the light brightness itself.

    The amount of energy emitted from it per second. That energy comes out in a form of photons which we can crudely represent with rays of light coming out of the source. The higher the power the more rays emitted from the source in a unit of time.

    Not all energy emitted is visible to the human eye, so we often rely on photometric measurements, which takes in account the sensitivity of human eye to different wavelenghts

     

     

    Details in the post
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    Read more: Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminance

LIGHTING