The photographs obtained using a zone plate in place of an objective, like pinhole photos, undergo significant digital noise and have a distinct character in comparison to that present on normal photographs obtained with an objective.

A zone plate is definitely more luminous than a pinhole, but remains anyway much less luminous than a traditional objective; therefore you often use the high sensitivity of the camera and/or lengthy exposure times. The images obtained are also very soft not only in terms of detail, but also contrast. Often therefore you apply levels and contrast curves in Photoshop in order to give energy to the photograph, while simultaneously amplifying the digital noise present in the image.

In the digital zone plate photographs and pinholes diagonal banding is often present.

The characteristics of the noise are extremely different from those seen in a traditional digital photograph. I have noticed, using both zone plates and pinholes, a strong diagonal banding at high frequency that crosses the entire image. In the shadows the noise then is intense and structured in an unusual way. The utilization of a program that filters the noise, such as Noise Ninja, does not produce the desired results, probably because the disturbance of the image does not occur at the frequencies for which the plug was designed.
In order to eliminate these artifacts a possibility is to apply a Gaussian filter, taking the noise out of focus and smoothing the image. The loss of detail in this case is almost always quite insignificant, considering that the zone plate photographs is already naturally very out of focus.

The visual characteristics of the noise of the photographs zone plate are deeply different from those obtained in the ordinary photographs rendering it difficult to be removed.

Another possibility is to add some grain in order to mask the digital noise. Personally this is a technique I prefer because in a completely out of focus image the grain creates a kind of constant to the eye in a word completely out-of focus, a steady structure allows a sort of system for visual reference to form.

When you add the digital noise in order to stimulate the grain of the film it’s essential to observe the result on a proof print, as the screen rendering causes an entire series of artifacts principally due to problems of aliasing. The images attached to this article are therefore only an indication. In each case, after many attempts with the original file, I have obtained optimal results on A3 size paper, using an Epson 2100 ink jet printer.

In the first place I have developed the raw file converting the photograph in black and white and playing considerably with contrast and curve. I completely burnt out highlights and set the shadows to pure lack, because what was interesting to me was the graphic effect and to amplify the impression of blinding light which is one of the characteristics of the zone plate photographs that attracts me more. The obtained obtained tonal range is typical of underexposed and overdeveloped films, that has a strong and intense grain.

A negative of the image applied as a layer mask gives a more natural grain on the picture.
Notice that in the mask, obtained as a simple negative of the original image, there are diagonal bands crossing the whole picture.

The resultin image, once opened in Photoshop, present a kind of noise that is very hard to remove and that looks badly. After removing all the dots correspond to grains of dust on the captor (in the case of zone plate and pinhole images, given the infinite depth of field, the dust on captor are all quite visible) I made a slight change of sharpen to make a drier noise. I then duplicate the layer and added a very strong monochrome Gaussian noise, more than I really needed, to have a good starting point.

In this way the noise evenly covers the image making it flat and not very bright. You see immediately that this is a uniform layer of noise superimposed to the photo, which does not looks as a real photographic grain, that instead constitute the image of silver salts when we use very sensitive film.

A simple and fast technique to have a nice effect is to simply add a mask to the layer with the uniform noise, to avoid add noise to the highlights.

In this way photography will mantein its contrast and brightness, and the uneven distribution of Gaussian noise looks as analog grain. To achieve this effect simply create a mask that is the negative of picture, and in the channels box, simply press ctrl and click on a channel, invert the selection, return to the pallet layer, make the layer which with the Gaussian noise active and add a layer mask.

The addition of grain covers the digital noise and produces a pleasing effect structuring the image.

Typically, this mask is too contrasted and needs some additional work, for example with the “levels” is easy to obtain the desired results. In general it is appropriate to make the black point a dark gray (using the “output” slide of the levels) in order to apply a minimum of noise even in high lights of the image. Following may be useful to intensify or reduce noise locally, lightening or darkening the layer mask. In this case, for example, I avoided to apply a too intense noise darkening the mask on the man body. To finish fine tune the final effect with the opacity of the layer.

With some experience you can understand the effect watching the picture on the screen, but, at least initially, is certainly appropriate to make print proofs. The final results is nice and realistic. There is the softness, the halos of light typical of zoneplate photographs, but the photographic structure consists of a nice, dry and well designed grain, very close to the the grain of old high sensitivity films.

Talking with Claudio Muzzetto about the article Local techniques of sharpening and noise reduction, we noticed the possibility of another passage that completely eliminates every kind of chromatic noise. The technique is used to reduce the color fringing, (colored halos between lights and shadows, generally due to chromatic aberrations), but can be successfully used to filter the chromatic noise. Once again, I suggest to download the images and observe them 100% zoom to notice the real effects obtained with the described technique.

Once arrived to the two-layers configuration described in the article quoted above, you would notice that some chromatic noise is still present inside the horizontal lines of the background, inside the girl’s pants and t-shirt. For the background, Noise Ninja correctly recognizes the edges, and to avoid a loss in details the plug-in doesn’t apply the filter in such zones. In the case of the t-shirt, the noise is probably recognized as detail; therefore once again Noise Ninja doesn’t filter the image in this point, leaving exactly some residual chromatic noise.

To avoid this problem, let’s move in this direction. Duplicate the Noise layer, which is the layer where noise has already been filtered with Noise Ninja. Name the layer as Anti color fringing and eliminate the level mask. Apply a slight Gaussian filter to the layer; usually an out-of-focus-ray between 2 and 4 pixels is enough. The image will be out-of-focus, but if you modify the blending option of this layer from normal to color, the residual chromatic noise will completely disappear and the image will be back in focus, thanks to the Sharpen Layer over the Anti Color Fringing Layer.

Using an out-of-focus layer in color blending option completely every residual chromatic noise, without loosing any detail.

The bigger the ray of the Gaussian Blur Filter the more the noise is canceled. At the same time though, if the image is plenty of zones where the color change from one to another, the saturation along those borders will decrease unpleasantly. As usual, we’re describing a compromise. In any case, it is possible to add a mask to avoid the application of this layer on some zones of the image. At this point you can head on as described in the quoted article, modifying the masks by hand, adding some monochromatic uniform noise, etc. The advantage is that no residual chromatic color will be yet present in the pic.

It is possible to automate all of these passages downloading the action set Noise and Sharpen.

Concerning analogical photography, once fixed the negative enlarger factor, the detail of a print is principally determined by a good shooting technique (absence of micro blur, correct focusing, correct depth of field and so on) and the resolving power of the shooting objective and the one on the enlarger. The image grain is determined by the film choice, exposition and development. Moreover the development allows controlling the acutance of the image. Furthermore, during the print phase, it is possible to modify both the detail and the picture grain, for example using contrast masks or out-of-focusing some zones with pantyhose interposed between the objective and the enlarger plan, but the interventions are long, laborious, hard to perform and have a somehow limited impact on the acutance and the image grain.

In the case of digital photography, shooting technique, objectives quality and exposition choice strongly influence the details and grain (or better: noise, as analogical grain and digital noise, even if similar, have different origin and characteristics). Anyway, the photographer now has two powerful instruments: sharpen filters and noise reduction filters.

Sharpen e noise reduction integrated in Camera Raw.

Unfortunately those instruments are often hidden to photographer or they are used mechanically and roughly. The consequence is that many old analogical photographers complain the noise and the absence of sharpness in digital images, thinking that it’s a defect inside the shooting system. Actually, this is largely due to the incorrect use of sharpen and anti-noise filters. The correct application of those instruments could bring to result similar to the ones the analogical photographers are used to or even better ones.

The article (in Italian) The sharpening, of whom I strongly suggest the reading, written by Andrea Olivotto, makes wonderful explanation of the digital techniques to control the acutance. It is a complete article, both for the introductive definition and for the advanced techniques, with tons of links to different articles, plug-ins and on-line resources. Russell Brown’s amazing website has a couple of video tutorials about sharpening, as well as on masks, that are intensely used in this article.

Talking about noise reduction, Noise Reduction Tool Comparison makes a complete confrontation of different software. Unfortunately, as software change (and ameliorate) frequently and quickly, the article is a little bit out of date, it would be better to take it as a list of possible software, software to be tested to find the one that better satisfy our needs. I once wrote an article on Camera Obscura about noise reduction as well: Add noise to eliminate noise.

Sharpen and noise reduction workflow

Noise Ninja application on the entire image with no sharpening filter.

Talking about my own workflow, first of all I put the sharpen and noise filter of Camera Raw to zero. Then I almost exclusively use the Smart Sharpen of Photoshop (go and see the finest Russel Brown’s tutorial at Smart Sharpen revealed) to manage the detail and Noise Ninja to reduce the noise. I use those filters because I know them well and the result completely fulfill me, but I’m not stating that this is the best combination. Anyway, the ideas exposed in the article – sharpening, noise reduction and the local application of the filters – can be well exploited no matter what kind of algorithm you will use to augment the acutance or reduce the noise of the image.

As any digital technique, there’s no manna from heaven that solves all of the problems automatically, otherwise it would be part of the firmware inside the digital camera. The most excellent results are obtained adapting the use of the instruments to the type of image on which you’re working and the type of result you’d like to achieve.

Depending on the case, I only use Smart Sharpen or Noise Ninja, possibly selecting the zones on the image where I can apply those filters. For example, I strongly apply Noise Ninja on skies, obtaining clear blues, even when the clouds contrast is augmented for retouch interventions. I apply only Smart Sharpen for detailed zones, such as gardens and hair.

Smart Sharpen filter application on an image with Noise Ninja already applied.

There are cases in which the manual procedure can be automated or completed by the use of surface and edge masks digitally generated. For this goal, I often use the TLR professional sharpening toolkit plug-in, which allows to obtain splendid results on images with both uniform and detailed zones. The results are particularly respectable, most of all when the masks are defined by hand, so that they completely adapt to the image. All these operations are effectuated on two copy layers of the background, one for sharpness and one for noise, where the masks are applied. This way it is possible to modify the intensity of the effect or the zones where the effect itself is applied.

In addition there are cases where this technique needs to be refined. Some images are particularly hard to work with and the choice of this or that software, the choice of the mask and so on are part of difficult compromises. Images with a strong noise, underexposed or shot on high iso sensibility, which still present highly detailed zones mixed with noise, such as sea surface or dresses, are particularly hard to be processed. In this tutorial I will show a solution that will use all of the quoted instruments and that will give back astonishing results in those complex cases.

Recovering wrong pictures

Smart Sharpen applied on the entire image. No noise reduction.

The image I used in this tutorial is part of a job I made some time ago. I set the camera “manual” to take some pictures of a location to paste in a stitch. Then the model straight a strange pose and I suddenly took a picture, without taking care to the exposure. As I was strongly underexposing the camera, I changed the parameters of the exposure, but the image I finally chose was the stolen image itself.

The only possibility in this case is a good editing effort, to turn the picture into a good work. I adjusted the general exposition with Camera Raw of even an entire stop, opening shadows with Fill Light command. I then managed the local contrast with Photoshop, augmenting it in different zones to entirely regulate the gamut of the picture. These operations obviously brought to a considerable and unacceptable augment of the noise. In this case is exceptionally hard to select the uniform zones to the detailed ones by hand, because an intricate mosaic constitutes the background. There are many lines that must be exalted and at the same time flat areas on which the noise is too evident. It is evidently a hyperbole; the best would be taking the picture again correcting the errors. From the didactic point of view though, this is an amazing opportunity to illustrate the technique we’re working on in this article.

The values of the filters and the used settings

Noise Ninja filter application of an image with Smart Sharpen already applied.

To compare the images, the filters have been applied with the same values. To obtain better result, it would be recommendable to accurately choose the parameters of each filter, but this is only a demonstration.

Noise Ninja, with the profile adequate to the ISO sensibility and the right camera model set, has been used with value 15 for strength and smoothness, both for luminance and color. Those relatively high values have been used to demonstrate the consequences of an aggressive use of the reduction noise filter. The contrast has been kept at 10 and sharpen filter at 0, to use Smart Sharpen only for acutance. Smart Sharpen has been used in its base version for a simpler learning, with 130 of amount and 0.8 of radius, kind of standard values for such dimensioned images. The TLR plug-in has been used to generate surface and edge masks, with High Resolution values for the camera and medium for Sharpen Width.

Noise and sharp layers with surface and edge masks respectively. Let’s notice that the blending option for the sharpen layer is luminosity.

Sharpen and noise reduction of Camera Raw have been set to zero and all of the operations have been done at 16 bit. Smart Sharpen and Noise Ninja have been applied under all the adjustment layers, which means that all the filter operations have been applied after the “developing” with Camera Raw and before the tonal corrections in Photoshop. At the end of your work, all the image versions have been flatten, converted to 8bit-sRGB and saved in JPEG format with 10 as compression value. The attached images are all cropped at 100% of the original image; no modification has been made to the native dimension of the picture. To comfortably compare all the images, I suggest downloading them and observing each on 100% zoom, as the aliasing effects could modify the acutance perception and the noise reduction. A compressed file with all the images of the article is available for the download (2.3 Mb).

Simple use of Noise Ninja and Smart Sharpen

Application of Smart Sharpen and Noise Ninja on two copy layers of the background. They also have a edge mask and a surface mask respectively generated from the TLR plug-in professional sharpen toolkit. The noise layer is under the sharpen layer, this last one with luminosity as blending mode.

The first image is the file without any filter. The chromatic noise is particularly annoying on pants, while in uniform background zones the luminance noise is irritating. The image is thick and less detailed because of the loss of sharpness due to the demosaicing process. To obtain an acceptable result, the noise must disappear from clothes, keeping at the same time the natural appearance that they are constituted of. Moreover, the background luminance should be reduced, without compromising its mosaic lines.

Just to be complete, this is the result you get using sharpen and noise reduction integrated in Camera Raw. The chromatic noise disappeared from pants, but their details too. More refined instruments will lead you to richer details. At the same time on the background there are artifacts that I find unpleasant, Noise Ninja is definitely more efficient.

Applying only Noise Ninja on the entire image, the result is amazing on uniform zones, but the algorithm keeps the sharpness of the background mosaic lines as well. Unfortunately though, the details of clothes are irreparably flatten, giving the picture a plastic and false aspect, particularly objectionable. The following application of Smart Sharpen allows to recover some acutance, but visibly augment the residual noise that hasn’t been filtered by Noise Ninja.

In like manner, applying only Smart Sharpen on the entire image doesn’t lead to any good result. The picture is sharpened but noise is amplified unacceptably. Using Noise Ninja after Smart Sharpen as well is disastrous.

Surface and edge mask usage

Edge mask generated by TLR professional sharpen toolkit plug-in. Let’s notice how part of the noise, both on the background and on the shirt, is interpreted from the plug-in as detail. Moreover, details and noise of pants are inextricably mixed.
The surface mask is equal but inverted.

Using Noise Ninja and Smart Sharpen together is one possible solution, trying to separate their effects so that the first one will be applied only on uniform areas and the second one only on the edges of the image. The difference compared to previous results is that no more filters are applied on the entire image. Where sharpen is applied noise reduction is not and vice versa.

TLR plug-in automatically generates some surface and edge masks. Two background-copy layers are created, one with surface mask and Noise Ninja and the other one on top with edge mask and Smart Sharpen. Please remember to put blend option to luminosity of the sharpen layer, so that the chromatic noise won’t be emphasized.

This kind of configuration used on our image allows satisfying results for the background, where the noise is almost completely gone from the flatten areas, while the mosaic lines are correctly accented from the sharpen. The shown example is only the result obtained automatically, adjusting Noise Ninja and Smart Sharpen values; varying layers opacity and ameliorating masks by hand you will achieve excellent results.

Excellent result anywhere, except in highly detailed zones, such as clothes. Augmenting the sharpen improves the acutance, but increases the noise and loose the fabric weft. Moreover TLR can’t generate a correct surface and edge mask. Noise and detail in this case are intimately related to each other and it is hard to separate them in a way that they can be filtered independently. Any solution will be a less satisfying compromise.

Augmenting the luminance detail filtering the chromatic noise

Same two-layers configuration without edge or surface masks.

Thinking about what is the noise, where is evident, which cases are annoying and what you would save of the image would bring to a satisfying solution. The first consideration you should do is that generally the chromatic noise is unpleasant, while the luminance noise, most of all if uniform, is in many cases acceptable. The second consideration is that noise is particularly visible in uniform areas of the image, while where the zone is detailed, even if noise is particularly intense, it always goes unnoticed. It could seem a banal statement, but it is good to underline that the luminance noise in highly detailed zones is rarely irritating.

To put in practice those ideas, let’s take the precedent configuration and simply eliminate the edge mask of the sharpen layer (also the noise layer mask could be eliminated, without the edge mask the surface one is completely unuseful), without forgetting that the blend option of the layer must be luminosity. Once again, compared to the firsts examples, the sharpen and noise reduction are applied separately. Both filters are applied to the totality of the image, but individually are applied to a blank copy of the background, therefore they doesn’t negatively interact as seen before.

Proceeding this way you obtain perfect details into clothes. The grain when visible is sharpen and pleasant, the chromatic noise disappeared but in the meantime the fabric weft is kept perfectly, the details of the fabric are set to the right value from the sharpening. Well, obviously the noise background, without the edge mask, augmented even in the flatten areas. Anyway, the grain obtained is defined and monochromatic, so much that the image could be acceptable without any other intervention.

If in some zones of the image a residual chromatic noise is still present, it is possible to eliminate it with a technique inspired to the one that eliminates the color fringing. The details are illustrated into the article Anti color fringing to eliminate the residual chromatic noise.

It is possible to automatize all of these passages downloading the action set Noise&Sharpen.

Local application of detail augment and noise reduction

Final image, with masks adjusted by hand, following the desired effect.

To obtain the best result ever, at this point it is necessary an intervention by hand on masks. For the definitive version of the image, I kept on pants the sharpen layer over the noise layer without any mask. On the shirt I only applied the noise reduction and no sharpen. I then added a slight Gaussian noise, as explained in the article Add noise to eliminate noise.

As far as background is concerned, I applied surface and edge masks automatically generated by TLR with a little of Dust&Scratches filter to smooth down a bit. This is because in noisy images the grain is interpreted from the plug-in as detail. At the same time, I turned the black zones of the edge mask into grey, so that the background has some details more and an insignificant grain, similar to clothes. Those forethoughts are necessary to avoid the plastic effect of the smooth surfaces obtained with aggressive passages of Noise Ninja. At the end of your work, some modification to the layer transparency to harmonize the image. Obviously the image is a pure example. Following your personal taste, clothes can be too sharpened and unnatural, you could dislike the grain on the background, etc. Anyway those are my personal choices, the important point is that you have two layers at your disposal over the background that make you obtain all of the desired effects, only varying opacity and masks.

In the complex, as the majority of the masks are generated automatically and that manual selections can be quickly done with laze and a shade of tenth pixel, the procedure for the local application of sharpen and the noise filter took at last 5 minutes. The results are astonishing if compared to the initial image. Pants are extraordinary detailed, background is smooth as if shot with 100 ISO and correctly exposed, the grain only give substance to the surfaces and is not visible if printed. The results are so convincing that I saved a shot that was completely wrong and I gave the work as the picture simply wasn’t exposed by the book.

Video tutorial

I realized a short video (in Italian) with a practical demonstration of the editing technique described in the article. This way, even the Photoshop beginner can see how to create surface and edge masks, how to generate sharpen and noise reduction layer, how to work with filters and how to modify the masks to modulate the plug-in effects.

[youtube S4Xth4QwRi4 nolink]

Even if digital pictures noise is often related to analogical films grain, it is generally aesthetically less pleasant than the second one and it is better do everything possible not to have noise. Apart from useful hints while taking pictures, there are many great post-production systems to filter noise keeping the best of the detail, such as Noise Ninja, also available as a Photoshop plug-in.

Noise Ninja works for the majority of situations; it cleans images from its uniform noise zones, such as skies, leaving the detailed parts of the image almost untouched. Moreover, if it is applied with a border mask, such as the one produced by the script TLR Sharpening Toolkit, and a little of manual work to ameliorate the protection mask, the results are excellent.

There are cases where results are not so good as exposed in the introduction. In fact, if the image has been shot with little light and it should have shadows opened and contrast augmented in photo editing, even with a 16-bit raw file, noise is too strong in the image, which is plenty of unaesthetic artifacts or, in jargon, the file crushes.

Applying a strong anti-noise filter all the artifacts are eliminated (even if some stains remain), but the image turns into some plastic aspect. I would like to point out that, even not using a protection mask (for a didactic aim) and applying the filter at the maximum of its power, all the details focused on the left are acceptable.

The application of a filter to remove the noise ameliorates only in a measure the situation. Applied in a weak way, it can’t eliminate the artifacts amplified by the photo editing. Applied in a strong way, it eliminates the noise but the stains of artifacts remain. The big problem is mostly that the picture looks plastic and fake. This smooth and unreal aspect unfortunately is more and more often visible on the Net and also in some publications of a certain level, symptom of a bad aesthetic taste of the author and of a scarce knowledge of the means of photo editing software.

The solution exists and is very simple. To find it, let’s think that the grain is not unpleasant itself, actually it donates body and matter to the image. I would like to eliminate the defects of the noise, without completely flatten the picture. The digital noise is unpleasant because:

• it augments the chromatic noise: pictures with a strong but monochromatic grain effect are pleasant; pictures full of colored pixels are awful.
• the noise is not uniform: the zones with photo editing have more intense noise, therefore the computer work is more evident.
• the strong application of photo editing not only augment the regular grain of the image, but also makes some other artifacts appears such as banding phenomenon, definitely less aesthetic than the analogical grain or the one simulated digitally.
• noise and grain are not the same; the first one is unpleasant, the second one is generally acceptable.

Adding a little of gaussian and monochromatic noise is useful to mask the remaining artifacts, adding a pleasant grain that recalls films and gives body to the picture.

A file with a uniform and monochromatic noise doesn’t have all those drawbacks. It is sufficient to eliminate the unpleasant noise, smoothing the file and adding a uniform noise to remove a sesation of plastic objects from the edited file. As easy as pie.

To obtain a pleasant result, artifacts must be completely eliminated applying a strong anti-noise filter, without hesitating in using maximum filters values. Not to damage the image, it is better to protect with a mask the zones where details must be maintained and where there’s no artifacts. To remove this kind of plastic effect it is recommended to add a slight monochromatic Gaussian noise (for example less than 1,50%). It is a digital noise, but it is small and uniform, so it will be like grain more than noise. In any case it will be an effect more aesthetic than the original noise amplified by the editing. This way the noise will be constant on the entire image, will recall the monochromatic grain of films and will avoid the unpleasant plastic effect of the anti-noise filters.

It actually eliminates the noise to add a slight simulated grain.

Note: to realize the differences, I suggest to download the three pictures and visualize them at 100%, because if the browser window is too small, the downsized picture creates aliasing effects that avoid what is described in the article.