Accurate Camera Colour within Lightroom

Obtaining accurate camera colour within Lightroom 5, in other words making the pics in your Lr Library look like they did on the back of the camera; is a problem that I’m asked about more and more since the advent of Lightroom 5 AND the latest camera marks – especially Nikon!

UPDATE NOTE: Please feel free to read this post THEN go HERE for a further post on achieving image NEUTRALITY in Lightroom 6/CC 2015

Does this problem look familiar?

Accurate Camera Colour within Lightroom

Back of the camera (left) to Lightroom (right) – click to enlarge.

The image looks fine (left) on the back of the camera, fine in the import dialogue box, and fine in the library module grid view UNTIL the previews have been created – then it looks like the image on the right.

I hear complaints that the colours are too saturated and the contrast has gone through the roof, the exposure has gone down etc etc.

All the visual descriptions are correct, but what’s responsible for the changes is mostly down to a shift in contrast.

Let’s have a closer look at the problem:

Accurate Camera Colour within Lightroom

Back of the camera (left) to Lightroom (right) – click to enlarge.

The increase in contrast has resulted in “choking” of the shadow detail under the wing of the Red Kite, loss of tonal separation in the darker mid tones, and a slight increase in the apparent luminance noise level – especially in that out-of-focus blue sky.

And of course, the other big side effect is an apparent increase in saturation.

You should all be aware of my saying that “Contrast Be Thine Enemy” by now – and so we’re hardly getting off to a good start with a situation like this are we…………

So how do we go about obtaining accurate camera colour within Lightroom?

Firstly, we need to understand just what’s going on inside the camera with regard to various settings, and what happens to those settings when we import the image into Lightroom.

Camera Settings & RAW files

Let’s consider all the various settings with regard to image control that we have in our cameras:

  • White Balance
  • Active D lighting
  • Picture Control – scene settings, sharpening etc:
  • Colour Space
  • Distortion Control
  • Vignette Control
  • High ISO NR
  • Focus Point/Group
  • Uncle Tom Cobbly & all…………..

All these are brought to bare to give us the post-view jpeg on the back of the camera.

And let’s not forget

  • Exif
  • IPTC

That post-view/review jpeg IS subjected to all the above image control settings, and is embedded in the RAW file; and the image control settings are recorded in what is called the raw file “header”.

It’s actually a lot more complex than that, with IFD & MakerNote tags and other “scrummy” tech stuff – see this ‘interesting’ article HERE – but don’t fall asleep!

If we ship the raw file to our camera manufacturers RAW file handler software such as Nikon CapNX then the embedded jpeg and the raw header data form the image preview.

However, to equip Lightroom with the ability to read headers from every digital camera on the planet would be physically impossible, and in my opinion, totally undesirable as it’s a far better raw handler than any proprietary offering from Nikon or Canon et al.

So, in a nutshell, Lightroom – and ACR – bin the embedded jpeg preview and ignore the raw file header, with the exception of white balance, together with Exif & IPTC data.

However, we still need to value the post jpeg on the camera because we use it to decide many things about exposure, DoF, focus point etc – so the impact of the various camera image settings upon that image have to be assessed.

Now here’s the thing about image control settings “in camera”.

For the most part they increase contrast, saturation and vibrancy – and as a consequence can DECREASE apparent DYNAMIC RANGE.  Now I’d rather have total control over the look and feel of my image rather than hand that control over to some poxy bit of cheap post-ASIC circuitry inside my camera.

So my recommendations are always the same – all in-camera ‘picture control’ type settings should be turned OFF; and those that can’t be turned off are set to LOW or NEUTRAL as applicable.

That way, when I view the post jpeg on the back of the camera I’m viewing the very best rendition possible of what the sensor has captured.

And it’s pointless having it any other way because when you’re shooting RAW then both Lightroom and Photoshop ACR ignore them anyway!

Accurate Camera Colour within Lightroom

So how do we obtain accurate camera colour within Lightroom?

We can begin to understand how to achieve accurate camera colour within Lightroom if we look at what happens when we import a raw file; and it’s really simple.

Lightroom needs to be “told” how to interpret the data in the raw file in order to render a viewable preview – let’s not forget folks, a raw file is NOT a visible image, just a matrix full of numbers.

In order to do this seemingly simple job Lightroom uses process version and camera calibration settings that ship inside it, telling it how to do the “initial process” of the image – if you like, it’s a default process setting.

And what do you think the default camera calibration setting is?

Accurate Camera Colour within Lightroom

The ‘contrasty’ result of the Lightroom Nikon D4 Adobe Standard camera profile.

Lightroom defaults to this displayed nomenclature “Adobe Standard” camera profile irrespective of what camera make and model the raw file is recorded by.

Importantly – you need to bare in mind that this ‘standard’ profile is camera-specific in its effect, even though the displayed name is the same when handling say D800E NEF files as it is when handling 1DX CR2 files, the background functionality is totally different and specific to the make and model of camera.

What it says on the tin is NOT what’s inside – so to speak!

So this “Adobe Standard” has as many differing effects on the overall image look as there are cameras that Lightroom supports – is it ever likely that some of them are a bit crap??!!

Some files, such as the Nikon D800 and Canon 5D3 raws seem to suffer very little if any change – in my experience at any rate – but as a D4 shooter this ‘glitch in the system’ drives me nuts.

But the walk-around is so damned easy it’s not worth stressing about:

  1. Bring said image into Lightroom (as above).
  2. Move the image to the DEVELOP module
  3. Go to the bottom settings panel – Camera Calibration.
  4. Select “Camera Neutral” from the drop-down menu:
    Accurate Camera Colour within Lightroom

    Change camera profile from ‘Adobe Standard’ to ‘Camera Neutral’ – see the difference!

    You can see that I’ve added a -25 contrast adjustment in the basics panel here too – you might not want to do that*

  5. Scoot over to the source panel side of the Lightroom GUI and open up the Presets Panel

    Accurate Camera Colour within Lightroom

    Open Presets Panel (indicated) and click the + sign to create a new preset.

  6. Give the new preset a name, and then check the Process Version and Calibration options (because of the -25 contrast adjustment I’ve added here the Contrast option is ticked).
  7. Click CREATE and the new “camera profile preset” will be stored in the USER PRESETS across ALL your Lightroom 5 catalogs.
  8. The next time you import RAW files you can ADD this preset as a DEVELOP SETTING in the import dialogue box:
    Accurate Camera Colour within Lightroom

    Choose new preset

    Accurate Camera Colour within Lightroom

    Begin the import

  9. Your images will now look like they did on the back of the camera (if you adopt my approach to camera settings at least!).

You can play around with this procedure as much as you like – I have quite a few presets for this “initial process” depending on a number of variables such as light quality and ISO used to name but two criteria (as you can see in the first image at 8. above).

The big thing I need you to understand is that the camera profile in the Camera Calibration panel of Lightroom acts merely as Lightroom’s own internal guide to the initial process settings it needs to apply to the raw file when generating it’s library module previews.

There’s nothing complicated, mysterious or sinister going on, and no changes are being made to your raw images – there’s nothing to change.

In fact, I don’t even bother switching to Camera Neutral half the time; I just do a rough initial process in the Develop module to negate the contrast in the image, and perhaps noise if I’ve been cranking the ISO a bit – then save that out as a preset.

Then again, there are occasions when I find switching to Camera Neutral is all that’s needed –  shooting low ISO wide angle landscapes when I’m using the full extent of the sensors dynamic range springs to mind.

But at least now you’ve got shots within your Lightroom library that look like they did on the back of the camera, and you haven’t got to start undoing the mess it’s made on import before you get on with the proper task at hand – processing – and keeping that contrast under control.

Some twat on a forum somewhere slagged this post off the other day saying that I was misleading folk into thinking that the shot on the back of the camera was “neutral” – WHAT A PRICK…………

All we are trying to do here is to make the image previews in Lr5 look like they did on the back of the camera – after all, it is this BACK OF CAMERA image that made us happy with the shot in the first place.

And by ‘neutralising’ the in-camera sharpening and colour/contrast picture control ramping the crappy ‘in camera’ jpeg is the best rendition we have of what the sensor saw while the shutter was open.

Yes, we are going to process the image and make it look even better, so our Lr5 preview starting point is somewhat irrelevant in the long run; but a lot of folk freak-out because Lr5 can make some really bad changes to the look of their images before they start.  All we are doing in this article is stopping Lr5 from making those unwanted changes.

Become a patron from as little as $1 per month, and help me produce more free content.

Patrons gain access to a variety of FREE rewards, discounts and bonuses.

Pixel Resolution – part 2

More on Pixel Resolution

In my previous post on pixel resolution  I mentioned that it had some serious ramifications for print.

The major one is PHYSICAL or LINEAR image dimension.

In that previous post I said:

  • Pixel dimension divided by pixel resolution = linear dimension

Now, as we saw in the previous post, linear dimension has zero effect on ‘digital display’ image size – here’s those two snake jpegs again:

Andy Astbury,wildlife in pixels,pixel,dpi,ppi,pixel resolution,photoshop,lightroom,adobe

European Adder – 900 x 599 pixels with a pixel resolution of 300PPI

Andy Astbury,wildlife in pixels,pixel,dpi,ppi,pixel resolution,photoshop,lightroom,adobe

European Adder – 900 x 599 pixels with a pixel resolution of 72PPI

Digital display size is driven by pixel dimensionNOT linear dimension or pixel resolution.

Print on the other hand is directly driven by image linear dimension – the physical length and width of our image in inches, centimeters or millimeters.

Now I teach this ‘stuff’ all the time at my Calumet workshops and I know it’s hard for some folk to get their heads around print size and printer output, but it really is simple and straightforward if you just think about it logically for minute.

Let’s get away from snakes and consider this image of a cute Red Squirrel:

Andy Astbury,wildlife in pixels,

Red Squirrel with Bushy Tail – what a cutey!
Shot with Nikon D4 – full frame render.

Yeah yeah – he’s a bit big in the frame for my taste but it’s a seller so boo-hoo – what do I know ! !

Shot on a Nikon D4 – the relevance of which is this:

  • The D4 has a sensor with a linear dimension of 36 x 24 millimeters, but more importantly a photosite dimension of 4928 x 3280. (this is the effective imaging area – total photosite area is 4992 x 3292 according to DXO Labs).

Importing this image into Lightroom, ACR, Bridge, CapOne Pro etc will take that photosite dimension as a pixel dimension.

They also attach the default standard pixel resolution of 300 PPI to the image.

So now the image has a set of physical or linear dimensions:

  • 4928/300  x  3280/300 inches  or  16.43″ x 10.93″

or

  • 417.24 x 277.71 mm for those of you with a metric inclination!

So how big CAN we print this image?

 

Pixel Resolution & Image Physical Dimension

Let’s get back to that sensor for a moment and ask ourselves a question:

  • “Does a sensor contain pixels, and can it have a PPI resolution attached to it?
  • Well, the strict answer would be No and No not really.

But because the photosite dimensions end up being ‘converted’ to pixel dimensions then let’s just for a moment pretend that it can.

The ‘effective’ PPI value for the D4 sensor could be easily derived from its long edge ‘pixel’ count of the FX frame divided by the linear length which is just shy of 36mm or 1.4″ – 3520 PPI or thereabouts.

So, if we take this all literally our camera captures and stores a file that has linear dimensions of  1.4″ x 0.9″, pixel dimensions of  4928 x 3280 and a pixel resolution of 3520 PPI.

Import this file into Lightroom for instance, and that pixel resolution is reduced to 300 PPI.  It’s this very act that renders the image on our monitor at a size we can work with.  Otherwise we’d be working on postage stamps!

And what has that pixel resolution done to the linear image dimensions?  Well it’s basically ‘magnified’ the image – but by how much?

 

Magnification & Image Size

Magnification factors are an important part of digital imaging and image reproduction, so you need to understand something – magnification factors are always calculated on the diagonal.

So we need to identify the diagonals of both our sensor, and our 300 PPI image before we can go any further.

Here is a table of typical sensor diagonals:

Andy Astbury

Table of Sensor Diagonals for Digital Cameras.

And here is a table of metric print media sizes:

Andy Astbury

Metric Paper Sizes including diagonals.

To get back to our 300 PPI image derived from our D4 sensor,  Pythagoras tells us that our 16.43″ x 10.93″ image has a diagonal of 19.73″ – or 501.14mm

So with a sensor diagonal of 43.2mm we arrive at a magnification factor of around 11.6x for our 300 PPI native image as displayed on our monitor.

This means that EVERYTHING on the sensor – photosites/pixels, dust bunnies, logs, lumps of coal, circles of confusion, Airy Discs – the lot – are magnified by that factor.

Just to add variety, a D800/800E produces native 300 PPI images at 24.53″ x 16.37″ – a magnification factor of 17.3x over the sensor size.

So you can now begin to see why pixel resolution is so important when we print.

 

How To Blow Up A Squirrel !

Let’s get back to ‘his cuteness’ and open him up in Photoshop:

Our Squirrel at his native 300 PPI open in Photoshop.

Our Squirrel at his native 300 PPI open in Photoshop.

See how I keep you on your toes – I’ve switched to millimeters now!

The image is 417 x 277 mm – in other words it’s basically A3.

What happens if we hit print using A3 paper?

Red Squirrel with Bushy Tail. D4 file at 300 PPI printed to A3 media.

Red Squirrel with Bushy Tail. D4 file at 300 PPI printed to A3 media.

Whoops – that’s not good at all because there is no margin.  We need workable margins for print handling and for mounting in cut mattes for framing.

Do not print borderless – it’s tacky, messy and it screws your printer up!

What happens if we move up a full A size and print A2:

Red Squirrel 300 PPI printed on A2

Red Squirrel D4 300 PPI printed on A2

Now that’s just over kill.

But let’s open him back up in Photoshop and take a look at that image size dialogue again:

Our Squirrel at his native 300 PPI open in Photoshop.

Our Squirrel at his native 300 PPI open in Photoshop.

If we remove the check mark from the resample section of the image size dialogue box (circled red) and make one simple change:

Our Squirrel at a reduced pixel resolution of 240 PPI open in Photoshop.

Our Squirrel at a reduced pixel resolution of 240 PPI open in Photoshop.

All we need to do is to change the pixel resolution figure from 300 PPI to 240 PPI and click OK.

We make NO apparent change to the image on the monitor display because we haven’t changed any physical dimension and we haven’t resampled the image.

All we have done is tell the print pipeline that every 240 pixels of this image must occupy 1 liner inch of paper – instead of 300 pixels per linear inch of paper.

Let’s have a look at the final outcome:

Red Squirrel D4 240 PPI printed on A2.

Red Squirrel D4 240 PPI printed on A2.

Perfick… as Pop Larkin would say!

Now we have workable margins to the print for both handling and mounting purposes.

But here’s the big thing – printed at 2880+ DPI printer output resolution you would see no difference in visual print quality.  Indeed, 240 PPI was the Adobe Lightroom, ACR default pixel resolution until fairly recently.

So there we go, how big can you print?? – Bigger than you might think!

And it’s all down to pixel resolution – learn to understand it and you’ll find a lot of  the “murky stuff” in photography suddenly becomes very simple!

Become a patron from as little as $1 per month, and help me produce more free content.

Patrons gain access to a variety of FREE rewards, discounts and bonuses.

Pixel Resolution

What do we mean by Pixel Resolution?

Digital images have two sets of dimensions – physical size or linear dimension (inches, centimeters etc) and pixel dimensions (long edge & short edge).

The physical dimensions are simple enough to understand – the image is so many inches long by so many inches wide.

Pixel dimension is straightforward too – ‘x’ pixels long by ‘y’ pixels wide.

If we divide the physical dimensions by the pixel dimensions we arrive at the PIXEL RESOLUTION.

Let’s say, for example, we have an image with pixel dimensions of 3000 x 2400 pixels, and a physical, linear dimension of 10 x 8 inches.

Therefore:

3000 pixels/10 inches = 300 pixels per inch, or 300PPI

and obviously:

2400 pixels/8 inches = 300 pixels per inch, or 300PPI

So our image has a pixel resolution of 300PPI.

 

How Does Pixel Resolution Influence Image Quality?

In order to answer that question let’s look at the following illustration:

Andy Astbury,pixels,resolution,dpi,ppi,wildlife in pixels

The number of pixels contained in an image of a particular physical size has a massive effect on image quality. CLICK to view full size.

All 7 square images are 0.5 x 0.5 inches square.  The image on the left has 128 pixels per 0.5 inch of physical dimension, therefore its PIXEL RESOLUTION is 2 x 128 PPI (pixels per inch), or 256PPI.

As we move from left to right we halve the number of pixels contained in the image whilst maintaining the physical size of the image – 0.5″ x 0.5″ – so the pixels in effect become larger, and the pixel resolution becomes lower.

The fewer the pixels we have then the less detail we can see – all the way down to the image on the right where the pixel resolution is just 4PPI (2 pixels per 0.5 inch of edge dimension).

The thing to remember about a pixel is this – a single pixel can only contain 1 overall value for hue, saturation and brightness, and from a visual point of view it’s as flat as a pancake in terms of colour and tonality.

So, the more pixels we can have between point A and point B in our image the more variation of colour and tonality we can create.

Greater colour and tonal variation means we preserve MORE DETAIL and we have a greater potential for IMAGE SHARPNESS.

REALITY

So we have our 3 variables; image linear dimension, image pixel dimension and pixel resolution.

In our typical digital work flow the pixel dimension is derived from the the photosite dimension of our camera sensor – so this value is fixed.

All RAW file handlers like Lightroom, ACR etc;  all default to a native pixel resolution of 300PPI. * (this 300ppi myth annoys the hell out of me and I’ll explain all in another post).

So basically the pixel dimension and default resolution SET the image linear dimension.

If our image is destined for PRINT then this fact has some serious ramifications; but if our image is destined for digital display then the implications are very different.

 

Pixel Resolution and Web JPEGS.

Consider the two jpegs below, both derived from the same RAW file:

Andy Astbury,pixels,resolution,dpi,ppi,Wildlife in Pixels

European Adder – 900 x 599 pixels with a pixel resolution of 300PPI

European Adder - 900 x 599 pixels with a pixel resolution of 72PPI

European Adder – 900 x 599 pixels with a pixel resolution of 72PPI

In order to illustrate the three values of linear dimension, pixel dimension and pixel resolution of the two images let’s look at them side by side in Photoshop:

Andy Astbury,photoshop,resolution,pixels,ppi,dpi,wildlife in pixels,image size,image resolution

The two images opened in Photoshop – note the image size dialogue contents – CLICK to view full size.

The two images differ in one respect – their pixel resolutions.  The top Adder is 300PPI, the lower one has a resolution of 72PPI.

The simple fact that these two images appear to be exactly the same size on this page means that, for DIGITAL display the pixel resolution is meaningless when it comes to ‘how big the image is’ on the screen – what makes them appear the same size is their identical pixel dimensions of 900 x 599 pixels.

Digital display devices such as monitors, ipads, laptop monitors etc; are all PIXEL DIMENSION dependent.  The do not understand inches or centimeters, and they display images AT THEIR OWN resolution.

Typical displays and their pixel resolutions:

  • 24″ monitor = typically 75 to 95 PPI
  • 27″ iMac display = 109 PPI
  • iPad 3 or 4 = 264 PPI
  • 15″ Retina Display = 220 PPI
  • Nikon D4 LCD = 494 PPI

Just so that you are sure to understand the implication of what I’ve just said – you CAN NOT see your images at their NATIVE 300 PPI resolution when you are working on them.  Typically you’ll work on your images whilst viewing them at about 1/3rd native pixel resolution.

Yes, you can see 2/3rds native on a 15″ MacBook Pro Retina – but who the hell wants to do this – the display area is minuscule and its display gamut is pathetically small. 😉

Getting back to the two Adder images, you’ll notice that the one thing that does change with pixel resolution is the linear dimensions.

Whilst the 300 PPI version is a tiny 3″ x 2″ image, the 72 PPI version is a whopping 12″ x 8″ by comparison – now you can perhaps understand why I said earlier that the implications of pixel resolution for print are fundamental.

Just FYI – when I decide I’m going to create a small jpeg to post on my website, blog, a forum, Flickr or whatever – I NEVER ‘down sample’ to the usual 72 PPI that get’s touted around by idiots and no-nothing fools as “the essential thing to do”.

What a waste of time and effort!

Exporting a small jpeg at ‘full pixel resolution’ misses out the unnecessary step of down sampling and has an added bonus – anyone trying to send the image direct from browser to a printer ends up with a print the size of a matchbox, not a full sheet of A4.

It won’t stop image theft – but it does confuse ’em!

I’ve got a lot more to say on the topic of resolution and I’ll continue in a later post, but there is one thing related to PPI that is my biggest ‘pet peeve’:

 

PPI and DPI – They Are NOT The Same Thing

Nothing makes my blood boil more than the persistent ‘mix up’ between pixels per inch and dots per inch.

Pixels per inch is EXACTLY what we’ve looked at here – PIXEL RESOLUTION; and it has got absolutely NOTHING to do with dots per inch, which is a measure of printer OUTPUT resolution.

Take a look inside your printer driver; here we are inside the driver for an Epson 3000 printer:

Andy Astbury,printer,dots per inch,dpi,pixels per inch,ppi,photoshop,lightroom,pixel resolution,output resoloution

The Printer Driver for the Epson 3000 printer. Inside the print settings we can see the output resolutions in DPI – Dots Per Inch.

Images would be really tiny if those resolutions were anything to do with pixel density.

It surprises a lot of people when they come to the realisation that pixels are huge in comparison to printer dots – yes, it can take nearly 400 printer dots (20 dots square) to print 1 square pixel in an image at 300 PPI native.

See you in my next post!

Become a patron from as little as $1 per month, and help me produce more free content.

Patrons gain access to a variety of FREE rewards, discounts and bonuses.

Bit Depth

Bit Depth – What is a Bit?

Good question – from a layman’s point of view it’s the smallest USEFUL unit of computer/digital information; useful in the fact that it can have two values – 0 or 1.

Think of it as a light switch; it has two positions – ON and OFF, 1 or 0.

bit, Andy Astbury, bit depth

A bit is like a light switch.

We have 1 switch (bit) with 2 potential positions (bit value 0 or 1) so we have a bit depth of 1. We can arrive at this by simple maths – number of switch positions to the power of the number of switches; in other words 2 to the 1st power.

How Does Bit Depth Impact Our Images:

So what would this bit depth of 1 mean in image terms:

Andy Astbury,bit depth,

An Image with a Bit Depth of 1 bit.

Well, it’s not going to win Wildlife Photographer of the Year is it!

Because each pixel in the image can only be black or white, on or off, 0 or 1 then we only have two tones we can use to describe the entire image.

Now if we were to add another bit to the overall bit depth of the image we would have 2 switches (bits) each with 2 potential values so the total number of potential values, so 2 to the 2nd, or 4 potential output values/tones.

Andy Astbury,bits,bit depth

An image with a bit depth of 2 bits.

Not brilliant – but it’s getting there!

If we now double the bit depth again, this time to 4 bit, then we have 2 to the 4th, or 16 potential tones or output values per image pixel:

Andy Astbury,bits,bit depth

A bit depth of 4 bits gives us 16 tonal values.

And if we double the bit depth again, up to 8 bit we will end up with 2 to the 8th power, or 256 tonal values for each image pixel:

Andy Astbury,bits,bit depth

A bit depth of 8 bits yields what the eye perceives to be continuous unbroken tone.

This range of 256 tones (0 to 255) is the smallest number of tonal values that the human eye can perceive as being continuous in nature; therefore we see an unbroken range of greys from black to white.

More Bits is GOOD

Why do we need to use bit depths HIGHER than 8 bit?

Our modern digital cameras capture and store RAW images to a bit depth of 12 bit, and now in most cases 14 bit – 4096 & 16,384 tonal values respectively.

Just as we use the ProPhotoRGB colour space to preserve as many CAPTURED COLOURS as we can, we need to apply a bit depth to our pixel-based images that is higher than the capture depth in order to preserve the CAPTURED TONAL RANGE.

It’s the “bigger bucket” or “more stairs on the staircase” scenario all over again – more information about a pixels brightness and colour is GOOD.

Andy Astbury,bits,bit depth,tonal range,tonality,tonal graduation

How Tonal Graduation Increases with Bit Depth.

Black is black, and white is white, but increased bit depth gives us a higher number of steps/tones; tonal graduations, to get from black to white and vice versa.

So, if our camera captures at 14 bit we need a 15 bit or 16 bit “bucket” to keep it in.  And for those who want to know why a 14 bit bucket ISN’T a good idea then try carrying 2 gallons of water in a 2 gallon bucket without spillage!

The 8 bit Image Killer

Below we have two identical grey scale images open in Photoshop – simple graduations from black to white; one is a 16 bit image, the other 8 bit:

Andy Astbury,bits,bit depth,tone,tonal graduation

16 bit greyscale at the top. 8 bit greyscale below – CLICK Image to view full size.

Now everything looks OK at this “fit to screen” magnification; and it doesn’t look so bad at 1:1 either, but let’s increase the magnification to 1600% so we can see every pixel:

 

Andy Astbury,bits,bit depth,tone,tonal range,tonal graduation

CLICK Image to view full size. At 1600% magnification we can see that the 8 bit file is degraded.

At this degree of magnification we can see a huge amount of image degradation in the lower, 8 bit image whereas the upper, 16 bit image looks tonally smooth in its graduation.

The degradation in the 8 bit image is simply due to the fact that the total number of tones is “capped” at 256. and 256 steps to get from the black to the white values of the image are not sufficient – this leaves gaps in the image that Photoshop has to fill with “invented” tonal information based on its own internal “logic”….mmmmmm….

There was a time when I thought “girlies” were the most illogical things on the planet; but since Photoshop, now I’m not so sure…!

The image is a GREYSCALE – RGB ratios are supposedly equal in every pixel, but as you can see, Photoshop begins to skew the ratios where it has to do its “inventing” so we not only have luminosity artifacts, but we have colour artifacts being generated too.

You might look upon this as “pixel peeping” and “geekey”, but when it comes to image quality, being a pixel-peeping Geek is never a bad thing.

Of course, we all know 8bit as being “jpeg”, and these artifacts won’t show up on a web-based jpeg for your website; but if you are in the business of large scale gallery prints, then printing from an 8 bit image file is never going to be a good idea as these artifacts WILL show on the final print.

Become a patron from as little as $1 per month, and help me produce more free content.

Patrons gain access to a variety of FREE rewards, discounts and bonuses.