Best Practices to Insert Photos into A Document for Optimal Print

I’m working on a food menu (A4 size pages) and will be inserting a lot of photos of menu items.
How do I know what the best resolution/ppi is for a given photo?
What resolution should I make sure it is so it still looks good in print?

Put simply you would need to use 300 ppi photos to include in your compositions. The image’s resolution does not depend on how big the images are – whether it’s 4cm high or 7cm high, it doesn’t matter. What really matters is the expected viewing distance. Since you are working on a food menu, I presume that these would be placed on a restaurant table and guests would be reading these menus at about 30cm away (distance between eye and print), hence the 300 ppi figure.

For details on how to calculate these ppi values yourself, refer to our discussion on calculating the right resolution for prints.

Sure you can skimp on resolution to reduce strains on your computer. But if your menus comes out as blurry, would this turn away the guests? Of course that depends on whether it’s “fine dining” restaurant or street food. But I can assure you that when you don’t have enough pixels in your menu’s photos, your menu is going to look cheap.

Apart from resolution, you should also pay attention to color balance problems and make sure you fix them before giving the composition to the printing press. Sometimes images can be too red, blue-ish, or look washed out. Refer to our article on preparing images for printing for more details.

So go ahead, have a one-copy test print of your composition before ordering the whole batch for the entire restaurant. See if it looks good, test it under the lighting conditions of the restaurant at normal dining hours. If it looks blurry, too dark, or the color is a bit off, you can find the fixes are from this article.

How to Print Beach Banners from iPhone Snapshots

 

Need to print a 8×8 foot beach banner. Anyone know where I can get a picture of high enough resolution?

As banners that large typically would be observed at a distance of four feet (slightly more than a meter) or more, then a resolution of 72 dpi should be enough – refer to our article on calculating resolutions for prints for the exact formula. Translated to pixels, you would need an image with 6192 pixels wide and high — since this is a square image after all.  

The pixel count came from the following calculation:

8 feet * 12 inches/foot * 72 dots/inch = 6192 dots (pixels)

In megapixels, this would be an image of about 38 megapixels large – coming from multiplying 6192 pixels wide and 6192 pixels high. To put things into perspective, an iPhone 8 is able to capture 12 megapixels using its back-facing camera.

If you have a 38 megapixel camera (or better like the Phase One IQ1080), that’s great then you’re all set.

If not then you’re in a predicament. Don’t try to upscale it naively on your photo-editing app, which usually uses either bicubic interpolation or Lanzcos resampling.  Using those two “simple” algorithms to enlarge images for prints would likely create blurry outputs — which won’t be any better than handing out the original images to the vendor printing the banner.

Fortunately Bigger Picture can enhance images up to 8x without making it blurry. Hence you can use even a lowly iPhone to create 8-foot banners that looks sharp.

Simply load the image into Bigger Picture at and enter the desired pixel dimensions like the following screenshot.

Bigger picture beach banner 2x

Go ahead and see for yourself – try out Bigger Picture for less than a song.

BiggerPicture 1.1.6 Release Notes

BiggerPicture 1.1.6 fixes a number of crashes, security enhancements, and prepares the program for a future release of macOS.

Bigger Picture Italian

This release fixes a crash encountered whenever there is an error discovered while enhancing images.

Furthermore the release updates a number of libraries and updates the underlying programming language version. This should make the app better prepared for an upcoming release of macOS to be announced in the middle of this year.

We apologize if you were affected by that crash and thank you for sending in those crash reports.

BiggerPicture prepares photographs and graphics files for high-quality large format printing. The app prevents blurry images caused by low-resolution originals by using machine learning to enhance images and synthesize additional pixels to create sharp printouts for life-sized high-DPI finishes.

What is the Right Resolution for Life-Sized Prints?

One of our readers asked,

I came from a background of small print projects. Now I’m tasked to find photography art for five doors, each 12 x 14 inches. When it comes to finding images, I don’t know where to start. What would be the best size? Best resolution?

Printing press worker

For a start, there’s plenty of royalty-free images that you can find from Pexels, Pixabay, or Unsplash. Most photographs from these sources would have good lighting as well. Hence you just need to pick the ones which has enough pixels for your given print project.

Since our dear reader was looking for images to place on doors, I’m going to assume that people would view these images no closer than at an arm’s length. This would be about two feet or 24 inches.

Why does the distance matter? Image resolution is not just how many dots to put in a given inch (the dot per inch or pixel per inch metric), but also how far people would view them. The further the viewing distance, the less pixel density would be required such that people who view them doesn’t perceive the image as blurry, blocky, or otherwise be able to identify the individual pixels (dots) in the image.

What you need is a function that estimates the lower bound pixel density given an expected viewing distance. In other words, a formula that converts a distance in inches into a minimum dots-per-inch density value.

q = f(x)

 

Where:

  • x  — the expected distance between the viewer and the image, in inches.
  • q  — the minimum image resolution, in dots-per-inch or pixels-per-inch.

To derive the formula, first let’s draw a schematic of the problem. The image below shows a human eye (representing the viewer) that is looking at an image of height y at distance x. Now the angle that the eye makes between the bottom of the image and its top is . Let’s keep things simple and two dimensional for now, because making calculations for the width of the image would be exactly the same way, only on a different axis.

Eyesight model

We know that magazines are usually printed at 300 dpi (dots per inch). This resolution is effective when a person with normal eyesight is viewing it on a standard reading distance, which is one foot (12 inches). This is probably also the reason why the first retina-display iPhone debuted at that approximate pixel density, which is 326 ppi (pixels per inch). Similarly a retina-display MacBook Pro has only 220 ppi but looks just as good because of the longer viewing distance. Of course, some people has better eyesights and can appreciate higher resolution images whereas some others can’t tell the difference between iPhone 4 and iPhone 3G (before retina display) screens. But just take the middle ground for simplicity’s sake.

Now let’s plug in those standard numbers into our model. Let’s take an image of 1 inch high which is viewed at a distance of 12 inches. The image contains 300 pixels, which is the minimum required to “look good”.

Standard image model

Then we need to find angle that the eye makes between looking at the bottom and the top edge of the image. This would be useful to calculate the pixel per degree value later on. Using knowledge from high-school trigonometry, we get…

tan(⍺)  = y/x
tan(⍺)  = 1 inch / 12 inch

⍺ = arctan(1/12)
⍺ ≅ 4.76°

 

We’ll define p as the pixel-per-degree ratio as follows:

p = q / ⍺ 

 

Where

  • p — the pixel-per-degree ratio
  • q — the number of pixels (or printed dots).
  •  — the angle which contains those pixels.

Our 1-inch image has the bare minimum of q=300 pixels (dots), making it a 300dpi image. Let’s plug those numbers in.

p = q / ⍺ 
p = 300 pixels / 4.76°
p ≅ 62.98 pixels/degree 

 

That means that for every degree of eye movement there need to be at least p ≅ 62.98 pixels between them so that the eye can’t differentiate the individual pixels.

Now we want an arbitrary distance x to calculate how many pixels q that our 1-inch image can look acceptable. We solve the two equations above for the value of q.

p = q / ⍺ 
q = p * ⍺

⍺ = arctan(y/x)
q = p * arctan(y/x)

 

We already know the following values derived from our standard model of 1 inch image at a resolution of 300 pixels per inch viewed at 12 inch distance.

y = 1 inch
p = 62.98 pixels / degree

 

Plug those numbers in and you get the formula to calculate the minimum resolution given an expected viewing distance. This is the formula that we’ve been looking for, the function to convert a viewing distance to a minimum pixel density value.

q = 62.98 * arctan(1 / x)

 

Where

  • q — the minimum resolution in pixels or dots per inch.
  • x — the expected distance between the image and the viewer.

Then let’s go back to our dear reader’s initial problem. He/she would need to find images to fill 12 * 14 inch surfaces on doors. We’re assuming people won’t observe these doors closer than an arm’s length (or otherwise risking getting hit by the door if someone else is opening it from the other side), thus the viewing distance is about 24 inches (two feet).

q = 62.98 * arctan(1/24) ≅ 150 pixels per inch.

 

Given these we can calculate the minimum pixel dimensions of the images for the doors:

width  = 12 inches * 150 pixels per inch = 1800 pixels
height = 14 inches * 150 pixels per inch = 2100 pixels

 

Fortunately most images in Pexels, Pixabay, or Unsplash has more pixels than the minimum dimensions above and thus would look good to be printed on doors.

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BiggerPicture 1.1.5 Release Notes

BiggerPicture 1.1.5 is all about improving the application’s stability.  There were a number of cases where the app crashes due to a logic issue and this has been fixed. Thank you for sending in those crash logs!

We apologize for any inconvenience.  However, if the app does crash, please allow the app to send the crash log.  On next launch just after a crash, the app might ask for your permission to send crash logs — if you haven’t granted the permission earlier. Please enable this and allow the app to automatically send crash information so that it would help us in diagnosing your issue and prevent the app from crashing again.

Comparison between Preview and BiggerPicture

BiggerPicture is a macOS application that helps you prepare photographs and other imageries for high-quality large format printing. The app uses artificial intelligence to enhance images and create larger version of the image by filling the gaps between pixels through machine hallucination. Unlike most standard picture enlargement algorithms, the resulting image would not be blurry nor blocky — but sharper than the original.