Smooth Textured Photos

Scan Correct Color Smooth Texture Reduce Noise Remove Dust Repair Crop

I felt like a mad scientist with all the texture removal testing I performed!

I was trying to find a good solution for the scans of textured prints. The scanned images were mottled with an ugly discolored texture embedded in the image. Often the discoloration would be a sickly shade of yellow. The worst kind of textured prints had regularly spaced patterns of tiny dimples physically imprinted (embossed) into the photo paper. Scans of these dimpled photos resulted in the dimpled pattern to deeply embed itself into the scanned images.

After some testing, I found that the descreening filter in scanning software worked well to remove this mottling, although it left the scanned images a tad blurry. Luckily, I have discovered some top notch texture removal tools through trial and error as well as online research.

FFT filters are the best tools for removing embedded patterns. These patterns are often found in scans of prints that have regularly spaced rows of thousands of very tiny dimples, all the same size and shape. While Photoshop Elements does not have a built-in FFT noise filter, third-party FFT filters are available as Photoshop plugins. Also, Affinity Photo has a built-in FFT filter that works quite well.

Noise filters work great at removing random textures. Random textures are found in scans of prints with rough surfaces but without patterns.

Finally, blur filters work well to remove any residual texture, such as coarse noise left over from noise removal, or faint lines that remain after pattern removal.

A quick bit of testing has revealed the optimum order of steps:
FFT filter -> noise filter -> blur filter

Easy-as-ABC Instructions for Removing Texture from a Photo




Do This Step
if there is a regularly-spaced pattern embedded in the scanned image

Skip This Step
if you don't have an FFT filter, or the embedded texture is random (ugly dots all over, chaotic discoloration)

Step A: Remove Pattern Texture

Step A1: Deselect Areas Prone to Developing a Pattern

Sometimes pattern-free areas of solid white or bright colors develop faint patterns after using an FFT noise filter. Unfortunately, it isn't possible to predict which images will have this problem. If you find this problem happens to your image, simply undo the FFT filter, deselect the problem areas, and use the FFT filter again.

Below is an example of a pattern-free area developing a faint pattern. The "before" image shows a strong pattern on the blue pants and barely a hint of a pattern on the arm. The "after" image shows most of the pattern has been removed on the pants, but the arm developed a noticeable pattern. The solution was to deselect the arm before using the FFT filter. The third image shows how well the solution turned out. The pattern is barely visible on both the pants and the arm.
before FFT filter after FFT filter arm deselected, then filter

Step A2: Use FFT Noise Filter to Remove Embedded Pattern

Embedded patterns are caused by scanning in photos printed on photo paper embossed with a regularly spaced pattern. Typical patterns consist of rows of thousands of tiny dimples, all the same size and shape. An FFT noise filter is the best way to remove embedded patterns in scanned images.

Open up your FFT noise filter. You should see a place to enter settings. The following settings are recommended. Any settings that your FFT filter does not support can be ignored. The brush size (width) is the most important setting.
Setting Value
Width 6
Opacity 100% (default) as anything less will cause more pattern to remain
Flow 100% (for faster brush strokes)
Hardness 100%
The FFT noise filter window contains a large box consisting of thousands of faint pixels. A few of these pixels clump together forming a regularly spaced pattern of bright stars. Some stars will have horizontal and vertical lines and some stars will just look like spots. The pattern of stars corresponds mathematically with the pattern embedded in the image. The large box of stars should resemble the zoomed-in and zoomed-out boxes shown below, although the pattern may be a bit different.

The large box of stars should resemble the boxes shown below, although the pattern may be a bit different. The box on the left is shown zoomed in, so only the main stars near the center are shown. The box on the right is shown fully zoomed out, so all of the stars are shown. (Zoom out with Affinity Photo by using the Option key and the mouse scroll wheel.)

To remove the embedded pattern in your image, you must paint over the stars with your brush. Use an appropriately shaped cross or dot using a brush size of 6. For bright stars with long vertical and horizontal lines, you may need a cross shaped like a plus sign. For smaller stars, a nubby little cross may be enough. For tiny spots far from the center, a single dot might do.

Avoid drawing along the bright central lines, and avoid the central area altogether. The central lines and central area are where most of the image details are.

Shown below is a FFT box zoomed in and the same FFT box zoomed out. Below that is an enlargement of the same zoomed-out FFT box covered in various shapes of crosses and even a few dots. You can see how different shapes of crosses were used to just cover the bright parts of the stars with a bit of overlap.
FFT box (zoomed in) FFT box (zoomed out)
stars crossed out
Once you have covered all the stars with crosses, simply click Apply and you'll find most of the embedded pattern has auto-magically disappeared! What remains is random noise and a small amount of residual pattern. The noise and residual pattern can be removed in steps B and C.



Shown below is a closeup of a scanned image with a strong pattern texture. From a previous attempt at using an FFT filter on this image, pattern-free areas prone to developing a pattern were identified. These areas were a woman's face (shown below), as well as her arms and bright white objects (not shown).

The pattern-free areas were deselected, then an FFT filter was opened and all the stars were crossed out like the big box above. Shown below is the result of using the FFT filter.
before
after FFT filter
The vast majority of the pattern has been removed, revealing hidden detail. Notice the vertical lines on the left door trim. They were mangled by the pattern before, but are now quite noticeable.

While the pattern has mostly vanished, there is still a lot of random texture in the form of noise and discoloration to remove. Most of it can be removed in step B.
Good News: Hidden detail is revealed!    Bad News: So is hidden noise.



Do This Step
if there is a random texture embedded in the scanned image (anti-fingerprint, etc), or if there is any noise or discoloration, or any leftover pattern texture from step A

Skip This Step
if pigs can fly

Step B: Remove Random Texture

A noise filter won't be able to remove pattern texture, but can remove most random texture, film grain, noise, and discoloration. Any residual texture left over from this step can be cleaned in step C.

After running any noise filter, I suggest comparing before and after. Check whether enough noise is removed, whether low contrast areas are smeared, and whether fine details are lost.

If you have Topaz DeNoise, please see step B1.
If you have Photoshop Elements, please see step B2.


Step B1: Use Topaz DeNoise (skip step B2)

Full instructions for this filter can be found at Reduce Noise
Abbreviated instructions and sample values are below.

Under PRESETS, select "DeNoise 5 Presets". Then select a preset depending on how noisy the image is, usually anywhere from RAW-Light to RAW-Strongest. Then adjust sliders for special cases, as explained in the table below.
Slider Special Case
Overall Strength increase for extremely noisy images
Adjust Highlight increase for noisy walls
Adjust Shadow decrease to retain small details (eyes, teeth, etc)
Adjust Color - Blue increase for noisy skies
Adjust Color - Red decrease for smeared red shirts
Add Grain increase to add texture to overly smooth objects (walls, ground, etc)
The closeup shown below is from an image that had its embedded pattern mostly removed from an FFT filter. The FFT filter worked very well to remove the pattern but left a lot of noise and discoloration. Because of the amount of noise left, I started with a preset of RAW-Strong in Topaz DeNoise. This left the edges of tiny details (such as the clock face and the light fixture) a bit blurry, so I tried a preset of RAW-Moderate.

RAW-Moderate left the edges of tiny details noticeably less blurry than RAW-Strong. However, it left hundreds of faint specks especially in dark areas. I decided to raise Shadow from its starting value of .43. I raised it little by little until by the time I reached .7, the specks in the dark window and shadows faded. Applying the filter resulted in the image shown below.
before
after Topaz DeNoise
Her hair turned out slightly blurry, but the overall result looks awesome! A massive amount of noise, discoloration, and specks have vanished. Important details in the face (such as the eyes and mouth) are still well-defined. And those vertical lines in the trim are still there and straighter than before.


Step B2: Use Photoshop Reduce Noise. (skip step B1)

Full instructions for this filter can be found at Reduce Noise
Abbreviated instructions and sample values are below.

Many textured prints have discolored dots covering the image and these dots are usually but not always yellowish. Reduce Color Noise can remove most of the color noise but can cause unwanted color changes. Raise Reduce Color Noise high enough to remove discoloration but not so high that eyeballs turn red and rings turn gray.

To remove luminance noise, set Strength from 2 to 10 depending on how noisy the image is. Adjust until you find a good balance of removing most of the noise while retaining most of the detail.
Setting Value
Strength from 2 to 10 depending on noise
Preserve Details almost always 10% for textured photos
Reduce Color Noise 
  • 0% if no discoloration
  • 50% good starting value
  • raise to remove more color noise
  • lower if unwanted color changes occur
The closeup shown below left is from a photo of a Honda motorcycle, which was developed and printed backwards by the company that processed the film. The photo was printed on photo paper with an anti-fingerprint texture. This kind of texture is random, so an FFT filter won't help, but a noise filter will.

Since the motorcycle was covered in color noise, I tried the maximum value of 100% for Reduce Color Noise. While 100% helped a lot with the rivers of discoloration, it also removed a lot of color from the leafy ground cover in the background. So I lowered it to 50% and found that was a nice balance. The discoloration disappeared while the leaves kept most of their color.

Because of the heavy noise, I started with a Strength of 6 and quickly worked my way up to 10 which is the maximum. This photo needed it.

I set Preserve Details to 10% as that is an excellent number to use for most textured photos. The 10% value worked great for retaining edges of motorcycle parts while removing most of the noise.

Clicking Apply resulted in the closeup shown below right.
before after PS Reduce Noise
Using such large values for Strength and Reduce Color Noise helped considerably. While there is still some noise left, the photo looks a lot better. Any remaining noise can be smoothed out in step C, if desired.
!retteb hcum oS



Do This Step
if there is any coarse noise left over from noise removal, or if there are any faint lines that remain after pattern removal

Skip This Step
if your awesome noise filter removed all the noise in step B

Remove Residual Texture

According to Adobe®, the Surface Blur filter can be used to remove noise or grain. Indeed, Surface Blur is awesome for removing noise and grain, and works great for removing leftover texture as well. The reason it works so well is that the filter can blur all the graininess while leaving the edges of objects alone.

The Threshold setting controls how much edges of objects are affected by Surface Blur. Theoretically, the threshold controls how much neighboring pixels must differ from the center pixel before becoming blurred. Realistically, this controls how much object edges are blurred.

Threshold can vary from 2 to 255, though 10 is a great number to start with. Ten allows for most of the noise to be blurred while retaining sharp edges of objects. Sometimes edges will appear too sharp when using this filter! If this happens, a higher threshold (such as 15 or 20) will work well to soften the edges. Coarse noise may also require a higher number.

The Radius setting controls how large of an area is sampled for blurring. Realistically, this affects how blurry the result will be. Two is a good number to start with. The radius can be increased if the noise is too coarse or too much noise remains, or it can be decreased if the image gets too blurry.

If only certain areas have noise that needs to be blurred, this filter can be used selectively. Simply select the noisy areas using magic selection or lasso tools and then use this filter. Be careful of objects with fine details such as eyes/nose/lips/teeth, hair, and clothes.

Here's a table that shows the results of all my mad experiments. The values for Radius may work best if you've scanned your prints at 600dpi. You may or may not have to raise/double the radius for 1200dpi scans, or lower/halve the values for 300dpi scans.
Setting Value
Radius Start at 2, raise for coarse or excessive noise, lower if the result is too blurry.
The list of radius values below have the following effects:
  1. Mild softening of texture, slight image blur.
  2. Blends and tones down the texture, moderately low image blur.
  3. Melts and hides the texture, moderately high image blur.
  4. Obliterates texture, very strong image blur.
Threshold   Start at 10, keep raising by 5 until noise is gone and object edges sufficiently softened.
The closeup shown below left is from a scan of a rough & bumpy print that has been cleaned with Photoshop Reduce Noise filter at full strength (for all settings). Although the discoloration is gone as is some of the noise, there is still a lot of coarse texture left. Not to worry. Surface Blur to the rescue!

I fired up Surface Blur for a first pass and tried various settings. I started with a radius of 2 and a threshold of 10. The edges of the pants and rake looked a bit jagged, so I raised the threshold to 15. This smoothed out the edges nicely. I then raised the threshold to 20 but couldn't really see a difference between 15 and 20, so I went back to 15.

With a radius of 2, I noticed that the skin still looked blotchy, so I raised the radius to 3. This value made everything else look a bit too blurry. A radius of 2 made everything look pretty good except for the skin. I decided that I would run a second pass just on the skin, so that I could go ahead and use a radius of 2 on the entire image.

The closeup shown below right is the result of a first pass of Surface Blur with a radius of 2 and a threshold of 15. A significant amount of texture noise has been removed while retaining a lot of the detail. The eyes have been softened a bit, but I consider this an improvement as they were previously somewhat deformed by coarse noise.
before Surface Blur
(after PS Reduce Noise)
after 1st pass of Surface Blur

As I expected, there is still some noise left on the skin. There are brown dots under the eyes, and the neck and arm are still slightly blotchy. To fix the blotchy skin will require another pass of Surface Blur, but this time selectively, so that just the skin is blurred.

To prepare for a second pass of Surface Blur, I selected all of the affected skin using the lasso tool. More specifically, I selected the entire arm and neck and parts of the face. I avoided the eyes, eyebrows, nostril openings, and mouth. I didn't want facial details to become any more blurred. The image to the right shows the area I selected, which is shown temporarily highlighted.

After selecting the area for the second pass, I fired up Surface Blur again. I again tried various settings starting with a radius of 2 and a threshold of 10. Just like the first pass, I noticed improvement when using a threshold of 15. The skin became much smoother without becoming blurry. There was no improvement when using a threshold of 20, so I set it back to 15. I tried a radius of 3 but immediately noticed how blurry the skin became, so I set it back to 2. I applied the filter and checked the results.

The second pass of Surface Blur took out the blotchiness on the skin but left 3 brown dots under the left eye and a dot on the nose. My eye was drawn to the dots, so I decided to blur them with a third pass of Surface Blur.

To prepare for a third pass of Surface Blur, I selected just the areas with the dots as shown highlighted in the image to the left. I started with a radius of 2 and a threshold of 10 as usual. This didn't quite make the dots disappear, so I raised the radius to 3 which obliterated the dots. A radius of 3 can smear details, but the selected area was too tiny to notice. I applied the filter and checked the results.

Shown below left is the image after the first pass of Surface Blur on the entire image. This is the same image shown above right, displayed here again for an easier comparison. Shown below right is the image after the second and third passes of Surface Blur on just the skin.
after 1st pass of Surface Blur after 2nd and 3rd passes
Selective use of Surface Blur has resulted in smooth skin without softening details in the face and other parts of the photo.
The measles cleared up fine, but the fingers remained stubbornly fused together.