How Big Can I Print It?

A VERY low resolution image (3 MPix) that would print surprisingly well

One of the things we have to wrestle with when we want to make a print is how big can I print this image and get good results? And how large should I print it? There is a lot of advice out there. Some of it is good.

Film vs. Digital

Virtually all images have to be scaled up for printing. The print you want to hang on your wall is many times larger than the sensor or piece of film you start from. Hardly any of us are shooting 8×10 negatives these days. Even if we are, we still usually want to make larger prints.

The technology has changed completely from the film days. Enlargement used to be optical. By adjusting the enlarger lens and the distance from the film carrier to the print surface, the image was blown up to the desired size. If the lens is good, it faithfully magnifies everything, including grain and defects. If the lens is cheap, it enlarges and introduces distortion and blurring.

Digital enlarging is a totally different process. A digital image is an array of pixels. My little printer at my studio likes to have 300 pixels/inch for optimum quality. So if I want to make an 8×10 print and I have at least 2400×3000 pixels, it will print at its best quality without changing a thing. Digital enlarging is a matter of changing the number of pixels.

Digital enlarging

But usually I want to print a larger size than the number of pixels I have. Here the digital technology gets interesting. And wonderful. Going back to my example, if I want to make a 16×20 print and maintain best quality, I would have to double the pixels in each dimension. It would have to go to 4800×6000 pixels.

Photoshop has the ability to scale the number of pixels in your image. There are several algorithms, but the default, just called “Automatic”, usually does a great job. Here is the difference from film: software algorithms are used to intelligently “stretch” the pixels, preserving detail as much as possible and keeping smooth transitions looking good. Lightroom Classic has similar scaling for making a print, but it is automatically applied behind the scenes. Smoke and mirrors.

The result is the ability to scale the image larger with good quality.

Print technology

In a recent article I discussed a little of how an inkjet printer makes great looking prints using discrete dots of ink. There are other technologies, such as dye sublimation or laser writing on photosensitive paper, but they are far less used these days.

It should be obvious, but to make a really big print, you need a really big printer, at least in the short dimension of the print. Really big printers are really expensive and tricky to set up and use. That is why most of us send large prints out to a business that does this professionally.

Why do I say the printer has to be big in the short dimension of the print? Past a certain size, most prints are done on roll feed printers. They have a large roll of paper in them. Say you have a printer that prints 44″ wide. The roll of paper is 44 inches wide and many feet long.

We want to take our same 8×10 aspect ratio image and make a 44×55 inch print. If it was film, we would require an enlarger with at least a 44×55 inch bed and a cut sheet of paper that is 44×55 inch. But an inkjet printer prints a narrow strip at a time across the paper. The heads move across and print a narrow 44 inch long strip of the image, the printer moves the paper a little bit, and it prints another narrow strip. Continuing until it has printed the entire 55 inch length. Then the printer automatically cuts off the print.

But if we naively follow the recommendations for optimum quality, we have to scale our poor little 2400×3000 pixel image up to 13200×16500 pixels. Even the best software algorithms may introduce objectionable artifacts at that magnification.

Viewing distance

Maybe we don’t have to blindly scale everything to 300 (or 360) pixels/inch.

A key question is: at what distance will the image be viewed? Years of studies and observation led to the conclusion that people are most comfortable viewing an image at about 1.5 to 2 times the image diagonal length. This lets the natural angle of the human eye take in the whole image easily. For the example we have been using of the very large print, people would naturally choose to view it from about 105 to 140 inches.

Along with the natural viewing distance there is the acuity of the human eye. I won’t get into detail, but the eye can resolve detail at about 1 arc minute of resolution (0.000290888 radians for the nerds). Simply, the further away something is, the less detail we can see.

Going through the calculations, if our audience is viewing the large print from 1.5 times the diagonal, it only has to be printed at 33 ppi! Finer detail than that cannot be seen from that viewing distance.

I have heard photographers who have images printed for billboards or the sides of a large building talk about inches/pixel. It would look like Lego blocks up close, but it looks sharp from where the viewer is.

Nature of the image

This is true unless the audience is photographers. They are going to get right up to the print, as close as their nose will allow, to see every blemish and defect. 🙂 But normal humans will view it from a distance.

There are modifications to the pixels vs. viewing distance calculations depending on the nature of the image. If the image contains highly detailed structure it will encourage viewers to come closer to examine it. If the image is very low contrast, smooth gradations, it could be even lower resolution.

Printing at the highest possible resolution that you can for the data you have is always a good idea.

Your mileage may vary

How big of a print can you make? It depends – don’t you get tired of hearing that? It is true, though. The real world is messy and simplistic “hacks” often don’t work well. It is better to understand things and know how to make a decision.

When it comes down to it, these are great times for making prints, even large ones. My normal print service lists prints as large as 54×108 inches on their price list. I know even larger ones are possible.

How big should you print? How big can you print?

Conventional wisdom is that scaling the pixels 2x each dimension should usually be safe. My camera’s native size is 8256×5504 pixels. Scaling an image 2x would be 16512×11008 pixels. This would be a “perfect” quality print of 55×36 inches on a Canon printer. I have yet to need to print larger than that.

Given the perceptive effects of visual acuity, I am confident I could create much larger prints. Larger than is even possible by current printers. And they would look good at a reasonable distance.

A key question is who are you printing for? A photographer or engineer will be right up to the print with a magnifying glass looking at each pixel. Most reasonable people will want to stand back at a comfortable distance and appreciate the image as a whole. Who is your audience?

Learn how to scale your image without artifacts and how to use print shapening to correct for problems. Know the perceptual effects of human visual acuity. This is part of the craftsmanship we have to learn in our trade. Given those tools, the rest is artistic judgment. With today’s equipment and careful technique and craftsmanship we can create wonderful results.

Your mileage may vary.

The image with this article is very small – 3 MPix. I would not have a problem making a 13×19 print of it. I doubt you could see the pixels.

Have you tried to make large prints? How did it go? Let me know!

Out of Gamut

Abstract image with serious gamut problems.

That seems like a strange thing to say. It’s not a phrase you hear in normal conversation. What can it mean? I have written some about how sensors capture color, but I realize I have not mentioned the gnarly problem of color gamut. Unfortunately, I have been bumping into the problem lately, so I had to re-familiarize myself with it. Some of my new work is seriously out of gamut.

What does gamut mean

Most writers avoid this or give overly simplified descriptions. I’m going to treat you as adults, though. If you really are someone who is completely afraid of technology you might want to skip to the end – or ignore the whole subject.

The concept of gamut is really pretty simple, but you need some specialized knowledge and you have to learn some new things about the world.

I have mentioned the CIE-1931 Chromaticity Diagram before. That sounds scary, but you have probably seen the familiar “horseshoe” diagram of colors. I recommend you watch this video to understand how it was derived and what it means. This is the diagram:

CIE-1931 Chromaticity Diagram

After a lot of research and a lot of measurement, scientists determined that this represents all possible colors a typical human can see. Just the hue – color – not the brightness.

Very simply, a gamut is just a representation of what part of this spectrum a particular device can reproduce or capture.

Show me

The next figure shows the horseshoe with some regions overlayed on it.

Add ProPhoto colour space as a "working color space" - Which feature do you need? - DxO Forums

There are 3 triangular regions labeled: sRGB, Adobe RGB, and ProPhoto RGB. They are called color spaces. The diagram is indicating all possible colors that each color space can represent. The smallest one, sRGB, is typical of a computer monitor. It is what will be used when you share a jpg image with someone. It is small but “safe”. We lose a lot of possible colors, but everyone sees roughly the same thing on all their monitors.

Let’s jump to ProPhoto RGB. You can see that it covers the largest part of the horseshoe. In other words, ProPhoto RGB has the largest gamut. It is the best we have for representing image color and most professional photographers use this now. Unless they are doing weddings. That is a different world.

They’re not ideal?

Unfortunately, these color spaces are an ideal. The ProPhoto color space is a model for editing images. No actual devices or printers can give us the entire ProPhoto RBG gamut. Not even close. Most can barely do sRGB.

Here is a diagram of the color space a Canon pro printer can do.

The small horseshoe, labeled 4, is the printer gamut. It is larger then sRGB (3) and, overall, a lot like AdobeRGB (2). Smaller than ProPhoto RGB, which is not listed here.

It looks pretty good, and in general it is. I use one of these printers. But look at what it does not do. Most greens and extremes of cyan and blue and purple and red and orange and yellow cannot be printed. Actually, almost no extremely saturated colors can be printed.

And it is not just printers. Most monitors, even very good ones, are somewhere between sRGB and AdobeRGB spaces. This cannot really be considered a fault of the monitors or printers. The physics and engineering and cost considerations prohibit them from covering the full ideal range.

Any of these colors that I use in an image, that can’t be created by the device I am using, are referred to as “out of gamut”. Outside of the color space the device can produce. This is what I have been running in to lately.

What happens

So what happens when I try to print an image with out of gamut colors? Well, it is not like it blows up or leaves a hole in the page instead of printing anything. Printers and monitors do the best they can. They “remap” the out of gamut colors to the closest they can do. As artists, we have some control over that process, as we will see in the next section.

But the reality is that these out of gamut colors will lose detail, be washed out and without tonal contrast. When we get to looking at the print, we will say “yech, that is terrible”. Then we need to do something about it.

What can we do about it

There are things to do to mitigate the problem. Here is where we need to understand enough about the technology to know what to do.

First, we have tools to help visualize the problem. Both Lightroom Classic and Photoshop have a Soft Proof view. It will simulate the actual output for a particular printer and paper. You can also view gamut clipping for the monitor. Yes, because of gamut problems you may not be seeing the image’s real color information on your monitor.

Both Lightroom and Photoshop have versions of saturation adjustments and hue adjustment. These can help bring the out of control colors back into a printable or viewable range. With practice we can learn to tweak these settings to balance what is possible with what we want to see.

But even if we give up and decide to print images with out of gamut colors, there are options. the print settings have a great feature called “rendering intent”. They are a way to give guidance to the print engine on how we want it to handle these wild colors. Several different rendering intents are available, but the 2 that are most commonly used are Relative and Perceptual.

Rendering Intents

I use Perceptual intent most often, at least in situations where the are significant out of gamut colors. Using the Perceptual directive signifies to the print driver that I am willing to give up complete tonal accuracy for a result that “looks right”. The driver is free to “squish” the color and tone range in proportional amounts to scale the whole image into a printable range. I don’t do product photography or portraits, so I am usually not fanatical about absolute accuracy. How they work this magic is usually kept as a trade secret. But secret or not, it often does a respectable job of producing a good output.

The other common intent is Relative. This basically prints the data without modification, except that it clips out of gamut colors. That sounds severe, but the reality is that most natural scenes will not have any significant gamut problems, so no clipping will occur.

This is a great intent for most types of scenes, because no tonal compression will take place.

The answer

The answer is “your mileage may vary”. Most images of landscapes and people will not have serious out of gamut problems. When you do, this information may help you get the results you want. When you have a problem, turn on the soft proofing and try the Relative and Perceptual rendering intents. Look at the screen to see if one is acceptable. If not, go back and play with saturation and colors .

Why do I have problems? Well, I’m weird. I have been gravitating to extremely vibrant, highly saturated images. I like the look I am trying to get, but it can be hard to get it onto a print. The image at the top of this article is a slice of an image I am working with now. It is seriously out of gamut. I need to work on it a lot more to be able to print it without loss of color detail. Ah, technical limitations.

Is Scaling Bad?

Heavily sharpened image. Many pixels damaged.

I have written about image sharpness before, but I was challenged by a new viewpoint recently. An author I respect made an assertion that gave me pause. He was describing that when you enlarge film it is an optical scaling but digital enlarging requires modifying the information. Implying that modifying information was bad. So I was wondering, is digital scaling bad?

Edges and detail

Let me get two things out of the way. When we are discussing scaling we only mean upscaling, that is, enlarging an image. Shrinking or reducing an image size is not a problem for either film or digital.

The other thing is that the problems from upscaling mostly are edges or fine detailed areas. An edge is a transition from light to dark or dark to light. The more resolution the medium has to keep the abruptness of the transition, the more it looks sharp to us. Areas with gradual tone transitions, like clouds, can be enlarged a lot with little degradation.

Optical scaling

As Mr. Freeman points out, enlarging prints from film relies on optical scaling. An enlarger (big camera, used backward) projects the negative on to print paper on a platen. Lenses and height extensions are used to enlarge the projected image to the desired size.

This is the classic darkroom process that was used for well over 100 years. It still is used by some. It is well proven.

But is is ideal? The optical zooming process enlarges everything. Edges become stretched and blurred, noise is magnified. It is a near exact magnified image of the original piece of film. Unless it is a contact print of an 8×10 inch or larger negative, it has lost resolution. Walk up close to it and it looks blurry and grainy.

Digital scaling

Digital scaling is generally a very different process. Scaling of digital images is usually an intelligent process that does not just multiply the size of everything. It is based on algorithms that look at the spatial frequency of the information – the amount of edges and detail – and scales to preserve that detail.

For instance, one of the common tools for enlarging images is Photoshop. The Image Size dialog is where this is done. When resample is checked, there are 7 choices of scaling algorithms besides the default “Automatic”. I only use Automatic. From what i can figure out it analyzes the image and decides which of the scaling algorithms is optimal. It works very well.

All of these operations modify the original pixels. That is common when working with digital images and it is desirable. As a matter of fact, it is one of the advantages of digital. A non-destructive workflow should be followed to allow re-editing later.

Scaling is normally done as a last step before printing. The file is customized to the final image size, type of print surface, and printer and paper characteristics. So it is typical to do this on a copy of the edited original. In this way the original file is not modified for a particular print size choice.

Sharpening

In digital imaging, it is hard to talk about scaling without talking about sharpening. They go together. The original digital image you load into Lightroom (or whatever you use) looks pretty dull. All of the captured data is there, but it doesn’t look like what we remembered, or want. It is similar to the need for extensive darkroom work to print black & white negatives.

One of the processes in digital photography in general, and after scaling in particular, is sharpening. There are different kinds and degrees of sharpening and several places in the workflow where it is usually applied. It is too complex a subject to talk about here.

But sharpening deals mainly with the contrast around edges. An edge is a sharp increase in contrast. The algorithms increase the contrast where an edge is detected.

This changes the pixels. It’s not like painting out somebody you don’t want in the frame, but it is a change.

By the way, one of the standard sharpening techniques is called Unsharp Mask. It is mind-bending, because it is a way of sharpening an image by blurring it. Non-intuitive. But the point here is this is digital mimicry of a well known technique used by film printers. So the old film masters used the same type of processing tricks to achieve the results they wanted. They even spotted and retouched their negatives.

Modifying pixels

Let me briefly hit on what I think is the basic stumbling block at the bottom of this. Some people have it in their head that there is something wrong or non-artistic about modifying pixels. That is a straw man. It’s as silly as saying you’re not a good oil painter if you mix your colors, since they are no longer the pure colors that came out of the tubes. I have mentioned before that great prints of film images are often very different from the original frame. Does that make them less than genuine?

Art is about achieving the result you want to present to your viewers. How you get there shouldn’t matter much, and any argument of “purity” is strictly a figment of the objector’s imagination.

One of the great benefits of digital imaging is the incredible malleability of the digital data. It can be processed in ways the film masters could only dream of. We as artists need to use this capability to achieve our vision and bring our creativity to the end product.

I am glad I live in an era of digital imaging. I freely modify pixels in any way that seems appropriate to me.

The Making of “Nothing Is Quite What It Seems”

surreal landscape

Today I’m going to discuss the making of this image. I created this abstract image titled “Nothing Is Quite What It Seems” from disparate elements put together to achieve the surreal landscape effect I wanted.

But as the title suggests, nothing is what it seems to be.

Base, Idea

When i saw the thing creating the basic silhouette shapes I knew it needed to be a scene of dead trees in a barren landscape. In reality, though, these shapes are actually cracks in ice on a frozen lake in Colorado.

I framed the scene up to isolate these 2 cracks that looked the most to me like dead trees. The “brush” in the foreground is the near edge of the ice, looking through to some rocks close under the surface.

The processing required some touch-up editing and some dodge and burn and contrast enhancement. There was a little hue-saturation enhancement to bring out more of the yellow rocks.

All of this was done as a smart object in Photoshop. Because I wanted to keep my options open I use smart objects a lot. They give me the freedom to come back and continue editing later. I don’t like to commit permanent changes.

Texture

With the basic form set, I started building texture. Tone adjustments in the smart object of the base layer helped. Bringing up the contrast brought forward more of the texture of the ice. This is the dimples and spots all over the image.

To abstract it a little more I used the oil paint filter in Photoshop to soften the edges and give it a more painterly and abstract look.

Color treatment

I knew I wanted to change the color palette and make it look like it could be in an abandoned homestead on the Colorado plains. But I also wanted to layer on more interesting texture. After trying many overlays I settled on a beautiful rusty truck panel. The image I used is part of a 1948 Coleman Truck. Pretty rare, and it was aging beautifully.

The truck had large rust patterns and also areas of old yellow and green paint. Using this to establish the colors across the image worked for me. This truck overlay is also handled as a smart object. Careful blending achieved the look I wanted without it looking like a rusty truck.

Finishing

The final polishing and tweaking takes a lot of time, even though it doesn’t make sweeping changes. As we used to say in software development, the first 90% of the project takes 100% of the schedule. The last 10% takes the other 100% of the schedule.

There was final dodging and burning to do, bits of masking and retouching. Of course, there was a little bit of final color tweaking to my satisfaction. One of the reasons I use a flexible workflow is that I am prone to tweak things after I have looked at them a while.

Process

A comment on my workflow. Although this is a fairly complex image, nothing is permanently locked down or committed. While writing this I was able to open up all the layers and smart objects and see everything about how they were processed. I could still go in and change or modify anything in the image. And I did make some tweaks. I told you I can’t leave images alone.

And as a very experienced Photoshop user I know new tools will be developed and I will learn new ways of doing things. These will lead to new ways to process images that I will want to take advantage of in the future.

This is the way I choose to work this way on most of my images. It doesn’t take longer and it preserves total flexibility. I need that. I change my mind often!

Summary

I like the finished image. It seems to be a surreal Colorado landscape of dead trees, but it contains no trees or plains or anything else that it appears to be. It is truly not quite what it seems. Is this more interesting than a straight shot of the ice?

Lightroom and Photoshop are powerful and addictive tools. Know when to use them and know when to stop. Otherwise you may never stop. It’s a great time to be doing imaging.

It’s Messy

Pairs of things

Despite the image some artists try to present, the artistic process is messy. At least, for me. It is not a clear, linear path from inspiration to end result. Sometimes things don’t work. We hit dead ends. We change our minds. Even after arriving at what I thought was the end product, I may decide I don’t like it. When people look at the result, they cannot see the messy way we got there.

Vague goals

I can’t speak for other artists, only myself. Most of the time I only have a vague notion of what I intend to achieve when I start an image. Sure, I may have a general idea, or a theme, or I may be thinking of a project I am working on. But that is a kind of an idea, not a plan. It is definitely not precise.

I hear artists describe having a definite plan from the beginning, with everything sketched out in detail. I sometimes envy them. But most of the time I think that sounds like a boring process. There is no room for inspiration on the spot. When I start pulling a final image together I often let what I see on the screen guide and inspire me to the end. I am glad I work in a medium that is very malleable.

So I guess I’m a bad artist because I don’t know for sure where I am going when I start a work. Or maybe this is the process that works for me. I like to be flexible and adaptive.

Evolving ideas

Another side of my adaptive process is that I am open to exploring new ideas as I go. Ideas tend to build on each other, spawning new ones or modifying what I was thinking. I often end up seeing an image in a completely different way from where I started.

For this to happen, I have to be open and receptive. Being locked into a rigid plan blocks this exploration and learning. I seldom hesitate to change my vision part way through the process. Even to discard an image because it no longer is shaping up the way I now see it.

You could argue that I would be more efficient to do my experimenting and work out my vision before starting to refine an image. Perhaps you are right, but that is what I had to do when I was designing major software projects as an Engineer. The reality is that I am too visual to do that now as an artist. I have to see it, then make modifications.

Mistakes

I freely admit I make mistakes. I don’t plan them, but I don’t necessarily see them as failures.

An “oops” is often followed by a “huh, that’s interesting; I wonder if I could use that?” Sometimes a mistake will open up a new view or thought process. It can make me see new possibilities.

These are often happy accidents. They can lead to a creative new end and maybe even a modification of my “style”. The result of a mistake is often a realization of something I could do but I’ve never thought of it before. It is unlikely the mistake creates a finished work that I love, but it informs a new direction I could explore. It is a growth opportunity.

Seeing new opportunities

Opportunity is a key word in this process. My background is a long history of realism. So it can be hard for me to “loosen up” and take an image in an unexpected direction.

To counter that, I often force myself to spend some time considering unusual processing or unlikely seeming combinations of images. Most of these experiments are failures, in the sense that they seldom make it to the final image. However, they can inform my vision. There may be some aspect of the processing that I like and work in to future images. Or it may encourage me to try something else along the same line that I do end up liking.

We live in great times for exploration. Our image processing tools are the best anyone has ever had. Our high quality digital images have the most detail and potential for post processing that has ever existed. The barriers to our vision are mostly internal. We just can’t see it or give our self permission to go there.

Failure to recognize

Have you ever viewed an image in your editing software and been really undecided about it? It is not what you wanted. Your instinct is to delete it. But something way in the back of your mind says to keep it for a while.

That happens to me. I have said before there is something cathartic about deleting images I don’t want to have around. But sometimes I need to keep them. To let them age a while. Or maybe to let my subconscious work on them a while.

Now realistically, most of the time, when I look at them later, I know there wasn’t really anything of interest there. But sometimes… That is the joy of this. Sometimes there is an undiscovered gem. Very rarely I look at one of these saved images and realize my subconscious was trying to show me something I did not perceive at the time. This particular image may not be great, but there is a realization there that can inform my work going forward.

That is an a-ha moment. A growth opportunity. After I get over beating myself up for not realizing the potential at the time I can add it to my repertoire of situations and patterns to look for. I have grown as an artist. Maybe it can even help me be more receptive while I am shooting.

The image with this article is one of those slow to recognize ones. Look it over and see how many pairs of things you can find. It amazes me. I did not consciously recognize that when I shot it, but I think that is what was drawing me to it.