COLOR

  • OLED vs QLED – What TV is better?

     

    Supported by LG, Philips, Panasonic and Sony sell the OLED system TVs.
    OLED stands for “organic light emitting diode.”
    It is a fundamentally different technology from LCD, the major type of TV today.
    OLED is “emissive,” meaning the pixels emit their own light.

     

    Samsung is branding its best TVs with a new acronym: “QLED”
    QLED (according to Samsung) stands for “quantum dot LED TV.”
    It is a variation of the common LED LCD, adding a quantum dot film to the LCD “sandwich.”
    QLED, like LCD, is, in its current form, “transmissive” and relies on an LED backlight.

     

    OLED is the only technology capable of absolute blacks and extremely bright whites on a per-pixel basis. LCD definitely can’t do that, and even the vaunted, beloved, dearly departed plasma couldn’t do absolute blacks.

    QLED, as an improvement over OLED, significantly improves the picture quality. QLED can produce an even wider range of colors than OLED, which says something about this new tech. QLED is also known to produce up to 40% higher luminance efficiency than OLED technology. Further, many tests conclude that QLED is far more efficient in terms of power consumption than its predecessor, OLED.

     

    When analyzing TVs color, it may be beneficial to consider at least 3 elements:
    “Color Depth”, “Color Gamut”, and “Dynamic Range”.

     

    Color Depth (or “Bit-Depth”, e.g. 8-bit, 10-bit, 12-bit) determines how many distinct color variations (tones/shades) can be viewed on a given display.

     

    Color Gamut (e.g. WCG) determines which specific colors can be displayed from a given “Color Space” (Rec.709, Rec.2020, DCI-P3) (i.e. the color range).

     

    Dynamic Range (SDR, HDR) determines the luminosity range of a specific color – from its darkest shade (or tone) to its brightest.

     

    The overall brightness range of a color will be determined by a display’s “contrast ratio”, that is, the ratio of luminance between the darkest black that can be produced and the brightest white.

     

    Color Volume is the “Color Gamut” + the “Dynamic/Luminosity Range”.
    A TV’s Color Volume will not only determine which specific colors can be displayed (the color range) but also that color’s luminosity range, which will have an affect on its “brightness”, and “colorfulness” (intensity and saturation).

     

    The better the colour volume in a TV, the closer to life the colours appear.

     

    QLED TV can express nearly all of the colours in the DCI-P3 colour space, and of those colours, express 100% of the colour volume, thereby producing an incredible range of colours.

     

    With OLED TV, when the image is too bright, the percentage of the colours in the colour volume produced by the TV drops significantly. The colours get washed out and can only express around 70% colour volume, making the picture quality drop too.

     

    Note. OLED TV uses organic material, so it may lose colour expression as it ages.

     

    Resources for more reading and comparison below

    www.avsforum.com/forum/166-lcd-flat-panel-displays/2812161-what-color-volume.html

     

    www.newtechnologytv.com/qled-vs-oled/

     

    news.samsung.com/za/qled-tv-vs-oled-tv

     

    www.cnet.com/news/qled-vs-oled-samsungs-tv-tech-and-lgs-tv-tech-are-not-the-same/

     

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    Read more: OLED vs QLED – What TV is better?
  • HDR and Color

    https://www.soundandvision.com/content/nits-and-bits-hdr-and-color

    In HD we often refer to the range of available colors as a color gamut. Such a color gamut is typically plotted on a two-dimensional diagram, called a CIE chart, as shown in at the top of this blog. Each color is characterized by its x/y coordinates.

    Good enough for government work, perhaps. But for HDR, with its higher luminance levels and wider color, the gamut becomes three-dimensional.

    For HDR the color gamut therefore becomes a characteristic we now call the color volume. It isn’t easy to show color volume on a two-dimensional medium like the printed page or a computer screen, but one method is shown below. As the luminance becomes higher, the picture eventually turns to white. As it becomes darker, it fades to black. The traditional color gamut shown on the CIE chart is simply a slice through this color volume at a selected luminance level, such as 50%.

    Three different color volumes—we still refer to them as color gamuts though their third dimension is important—are currently the most significant. The first is BT.709 (sometimes referred to as Rec.709), the color gamut used for pre-UHD/HDR formats, including standard HD.

    The largest is known as BT.2020; it encompasses (roughly) the range of colors visible to the human eye (though ET might find it insufficient!).

    Between these two is the color gamut used in digital cinema, known as DCI-P3.

    sRGB

    D65

     

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    Read more: HDR and Color
  • 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
  • Björn Ottosson – How software gets color wrong

    https://bottosson.github.io/posts/colorwrong/

     

    Most software around us today are decent at accurately displaying colors. Processing of colors is another story unfortunately, and is often done badly.

     

    To understand what the problem is, let’s start with an example of three ways of blending green and magenta:

    • Perceptual blend – A smooth transition using a model designed to mimic human perception of color. The blending is done so that the perceived brightness and color varies smoothly and evenly.
    • Linear blend – A model for blending color based on how light behaves physically. This type of blending can occur in many ways naturally, for example when colors are blended together by focus blur in a camera or when viewing a pattern of two colors at a distance.
    • sRGB blend – This is how colors would normally be blended in computer software, using sRGB to represent the colors. 

     

    Let’s look at some more examples of blending of colors, to see how these problems surface more practically. The examples use strong colors since then the differences are more pronounced. This is using the same three ways of blending colors as the first example.

     

    Instead of making it as easy as possible to work with color, most software make it unnecessarily hard, by doing image processing with representations not designed for it. Approximating the physical behavior of light with linear RGB models is one easy thing to do, but more work is needed to create image representations tailored for image processing and human perception.

     

    Also see:

    https://www.pixelsham.com/2022/04/05/bjorn-ottosson-okhsv-and-okhsl-two-new-color-spaces-for-color-picking/

    Read more: Björn Ottosson – How software gets color wrong

LIGHTING