Journey to the Sahara

On 11 May 2017, I was in Morocco, touring with a group of friends. This is what I recorded in my diary about a journey to the western end of the Sahara Desert.

Hôtel Riad la Maison Bleue, Fes, Morocco.

We left Hotel Riad Maison Bleue in Fes (above) at 0800 and arrived at our desert tent camp near the Algerian border 12 hours later, after crossing the Atlas mountains, which form the spine of Morocco running diagonally across the country, more or less north east to south west, with the highest peak at 4,360 metres.

The scenery changed from green farmlands south of Fes to an alpine plateau, which is snow-covered in winter but is used for grazing in summer. There are no fences, so shepherds tend the flocks of sheep and goats. What a mind-numbing existence they appear to have, alone all day with the animals, enduring all kinds of weather conditions and living in homes that look not so different to those images we see of refugee camps.

As the altitude increased, the mountains became arid, barren and rocky with dramatic hills and valleys. We finally emerged onto a desolate, stony plane that reminded me a little of the scenery along the Stuart Highway between Woomera and Coober Pedy. Now the weather had changed from pleasant sunshine to overcast, with a strong wind stirring up the dust.

We stopped at a little community somewhere and transferred to five Four Wheel Drive vehicles for the final 50 km drive to camp. The wind had picked up, and we plunged into a sand/dust storm that sometimes reduced visibility so that we could only see one or two of the centreline markings on the road.  That worry disappeared when we turned off the road onto a stony plane. The vehicles spread out, travelling in an impressive line, with the more distant ones disappearing into the gloom. This was accentuated by the impending sunset just an hour away.

Then we began to see sand drifts, which progressively increased in size, slowing progress. Unknown to us in the lead car, one of the following cars became briefly bogged in a sand drift. Then we crossed a final dune, and there was the camp, a circle of tents awaiting us, with a red carpet (!) barely visible, as its shag-pile served as an excellent sand catcher. The world of the camp was a muted shade of orange thanks to the dust and sand in the air. Nothing could be seen of the environment beyond the tents.

The full fury of the wind was revealed when we emerged from the car. Wind speeds of 47 km/h had been forecast, and we seemed to be experiencing their maximum intensity. I suddenly realised that traditional Arab clothing made so much sense. The one-piece overclothing has no places where sand can collect. The turban-come-scarf keeps sand out of the hair and ears and could be arranged to protect the face. But there was no way to protect the eyes from the stinging sand.

So here we were, on the western edge of the great Sahara Desert, and it had turned on a memorable welcome for us!

The Sahara Desert

We were welcomed in the customary way with a glass of hot tea, served by young Berber men in their traditional bright blue clothing. They then led us to our tents, but walking was difficult when leaning into the wind with eyes closed against the stinging sand.

The spacious, sturdy tents had inner and outer linings that shook and made disturbing noises under the onslaught of the wind, but the air was calm inside. An ensuite bathroom was discreetly hidden behind a curtain. Lighting and water supply were understandably basic, hot water being heated by a wood fire and the whole camp powered by PV panels.

Dinner was served, but I had a minimal amount of food, not wanting to further upset my Delhi-Belly. Then went to my tent to dust the sand off the bed, have a cleansing shower, and retire. Surprisingly, I had no trouble sleeping despite the 35-degree heat, the wind noise and the vibrations transmitted to the bed via the bedhead, which was against the windward-facing tent wall.

I woke at 0530 to the sound of hand clapping and shouts of, “Are you coming? It’s time for the camels.”  For a moment, I thought about going back to sleep, but remembered I was here because, during trip planning, I had identified it as a significant highlight. Emerging from the tent, I was surprised to see that the air was calm, the sky cloudless, and, in the desert silence, the predawn light was beautiful.

Me and my camel at Et-Taous. Note, no stirrups - Painful on the inner thighs!

After a fortifying espresso, we mounted the camels and wound our way up the dunes for 30 minutes to the highest dune, where we could observe the sunrise. The clear air revealed a sea of rolling dunes to the east. To the west was the almost full moon in a pastel-blue sky, streaked with soft clouds, above the stony plane we had crossed the previous day in the sandstorm. Dark rows of mountains lined the horizon. Absolutely breathtaking! So glad I didn’t stay in bed.

The dust storm and high winds had ‘groomed’ the dunes, leaving them in pristine condition with no trace of footsteps made by visitors on the previous day.

The view to the west before sunrise.

While everybody stood on top of a dune to watch the sunrise, I did what photographers do and looked in the opposite direction for memorable images. Noteably, our guides and camel handlers were waiting in a line on the edge of a dune - a perfect spontaneous composition for a photo. It was all over too soon.

Berber men in blue, Berber boy in white.

The camels took us back to camp, and we quickly made our way into the dining tent for breakfast. Before loading our gear into the cars for the return trip, we were fair-welled with a drum and singing performance by our Berber hosts, followed, of course, by the mandatory group photo.

Driving in the clear air, we saw that the landscape we had passed through yesterday, in the gloomy cloak of the dust storm, was dotted with isolated flat-roofed mud-brick houses set in the formidable stony landscape. What the people did for a living was a mystery, but there were small villages every now and then. Perhaps tourism is the answer. There were some struggling palms and a few low shrubs, but very little colour amongst the various shades of grey and brown.

We passed a boy standing on the roadside holding something above his head. It was a baby fox. We were told he would sell it as a pet.

How Camera Clubs Can Address the AI Dilemma

I used ChatGPT to respond to the following long prompt. A “conversation” ensued, part of which is copied below.

PROMPT: Camera clubs for amateur photographers have rules governing the photos that can be shown. These relate specifically to the authenticity of a photographer's images. Plagiarism is not allowed. Typical editing of digital images before the advent of AI was acceptable, but replacing the sky in an image with a different sky was acceptable, provided that both images were the photographer's own. Now, with generative AI, there is a need for more rules. Primary among these is the rule that an image, or part of an image, must not be created with a text prompt; after that, it becomes unclear to me. Many people accept that distracting parts of an image can be removed, provided that the area inserted is based on pixels from the surrounding areas. Traditional cloning and healing tools worked in this way, but with AI, it is unclear if that is the case. In Lightroom Classic, I have found that the remove tool without AI will sometimes make a mess of the removal, but with "Use generative AI" and "Detect Objects" selected, the result can be much better. The question is, did AI 'invent' the new area, or did it use pixels from the image? Super-sizing is another area of debate. Is the enlarged image a new image, or does it contain pixels derived from the original? In Photoshop, Generative Expand creates a new extension of the image that appears to be based on the original, but it is not the photographer's work. What guidance can you provide based on the documentation found online?

RESPONSE: A small but growing number of clubs and competitions are beginning to address the AI problem by separating competitions by editing philosophy rather than trying to police specific tools. This approach removes much of the ambiguity surrounding AI tools.

The model typically uses three clearly defined categories.

1. Straight Photography (or “Nature / Documentary”)

This is the strictest category, designed to preserve photographic authenticity.

Typical rule

The image must represent the scene as photographed. No elements may be added, removed, or relocated.

Allowed adjustments

  • exposure and contrast

  • colour balance

  • cropping

  • sharpening

  • noise reduction

  • minor dust spot removal

Not allowed

  • removing objects (people, branches, signs, etc.)

  • compositing

  • sky replacement

  • generative AI

  • significant cloning or healing

This model is widely used by organisations such as the Photographic Society of America and many nature competitions.

2. Altered Reality / Creative Photography

This category allows extensive editing and compositing, but still requires photographic origin.

Typical rule

All visual elements must originate from photographs taken by the entrant.

Allowed:

  • compositing multiple photographs

  • sky replacement (from the photographer’s own images)

  • object removal

  • creative colour grading

  • extensive cloning

Still not allowed:

  • text-prompt AI image generation

  • generative AI objects

  • stock images

  • images captured by someone else

The philosophy is:

creative manipulation is allowed, but the raw material must still be photography.

3. Open Digital Art / AI Art

Some organisations are now adding a third category.

Here almost anything is allowed:

  • generative AI

  • text prompts

  • stock elements

  • illustration

  • heavy digital painting

This category recognises that AI imagery is becoming a legitimate creative medium, but it is no longer treated as photography.

Why this system works

Instead of debating specific software tools, it focuses on creative intent.

Straight: Faithful representation.

Altered Reality: Creative photography.

Digital / AI Art: Image creation.

This structure prevents endless arguments about individual tools like:

  • generative remove

  • content-aware fill

  • AI upscaling

because the category's intent is clear.

An example rule set some clubs are adopting

Category A — Authentic Photography

Minimal editing only; the scene must remain unchanged.

Category B — Creative Photography

Extensive editing allowed, but all elements must be photographic captures by the entrant.

Category C — Digital / AI Art

Any digital techniques allowed.

Why this is becoming necessary

AI tools are improving extremely quickly. Within a few years, it will be very difficult to tell whether:

  • an object was cloned away

  • an object was generated

  • a sky was real or synthetic

By separating categories, clubs avoid the need to detect AI usage.

An additional rule that simplifies judging

Some competitions now include a declaration such as:

“Entrants must be able to supply the original capture file(s) for all photographic elements used in the image.”

This protects authenticity in the first two categories.

In effect, the emerging international standard is:

  • photography categories → no AI-generated scene content

  • AI categories → anything allowed

This preserves photography while acknowledging that AI image creation is a different medium.

The Use of AI in Camera Club Competitions

I asked ChatGPT a detailed question about the authenticity of photographs in camera club competitions. In brief, I discussed the available tools and how their use might affect authenticity. Here is the answer.

The uncertainty you describe is widely recognised in photography organisations and competitions. The key issue is whether a tool merely modifies existing pixels or generates new image content. Documentation from Adobe and commentary by photographic educators clarifies this distinction fairly well, even if the ethical rules used by camera clubs have not yet caught up. Below is a structured interpretation based on current documentation and common competition rules.

1. The critical distinction: analytical AI vs generative AI

Most modern software uses AI in two fundamentally different ways:

1. Analytical (non-generative) AI

• Examines the pixels already in the image.

• Adjusts, selects, or enhances them.

• Does not create new image content.

Examples:

• AI subject selection

• Sky masking

• Noise reduction

• Lens blur simulation

These tools analyse the image and then modify the existing pixel data. They do not invent objects or scenery. (matiash.com)

From an authenticity standpoint, these are usually considered equivalent to traditional editing.

2. Generative AI

• Creates new pixels that were not present in the original image.

• Uses trained models rather than simply copying neighbouring pixels.

Example tools:

• Generative Remove

• Generative Fill

• Generative Expand

• Text-prompt image generation

Adobe’s documentation explicitly states that Lightroom’s Generative Remove uses the Firefly generative AI model to generate new fill content after an object is removed. (Adobe Help Centre)

It even produces multiple variations for the user to choose from, which confirms that the replacement area is synthesised rather than copied from the photo. (PetaPixel)

For camera club authenticity rules, this is the dividing line.

2. Lightroom’s Remove Tool — three different technologies

Lightroom now combines three distinct mechanisms, which behave very differently.

Clone tool

• Direct pixel copying.

• Source area → target area.

Equivalent to classic cloning in Photoshop.

Authenticity status: Usually acceptable in competitions.

Heal tool

• Samples nearby pixels.

• Blends colour and tone from surrounding areas.

It still derives its content from the photograph itself. (Adobe Help Centre)

Authenticity status: Typically acceptable (traditional retouching).

Generative Remove

• Uses Adobe Firefly.

• Generates new pixels to fill the removed area.

The fill is not guaranteed to come from the image itself. (Adobe Help Centre)

Authenticity status: Many competitions now consider this AI generation, even though it is used for object removal.

3. Why generative removal behaves differently

Several clues reveal that generative AI is being used:

Multiple generated versions

Lightroom offers three alternative fills for the removed area. (PetaPixel)

Traditional pixel cloning could not produce multiple plausible scenes.

Internet connection required

The generative fill is often produced by a cloud model rather than local pixel analysis. (Michael Frye Photography)

Lower resolution patches

Generated areas may have slightly lower resolution than the surrounding image because they are synthesised rather than copied. (Michael Frye Photography)

4. Super-resolution and upscaling

Upscaling tools (e.g., Super Resolution in Lightroom or AI upscalers) occupy a grey area.

Technically, they do create new pixels, but those pixels are:

• mathematically inferred from the original image

• not arbitrary new content

The process estimates detail based on patterns in the existing data.

In practice:

Bicubic enlargement: Interpolates pixels mathematically, usually acceptable.

AI Super Resolution: Predicts fine detail, usually acceptable but debated.

Generative Expand: Invents entirely new scene content, usually not acceptable.

5. Generative Expand (Photoshop)

Generative Expand clearly crosses the authenticity boundary.

It can:

• extend landscapes

• create new sky, buildings, water, etc.

• fabricate entirely new visual content.

Although the style matches the image, the added scene elements were never photographed.

Most competitions would classify this as image creation rather than photography.

6. Why camera clubs are struggling

Traditional editing rules assumed a simple model:

Photograph → edit existing pixels

AI introduces a new model:

Photograph → generate new pixels

Because the output can look perfectly realistic, the boundary is no longer obvious.

7. How many photographic organisations are responding

Major competitions and salons increasingly define rules around image provenance, not just editing tools.

Typical modern wording:

Allowed

• tonal adjustments

• colour grading

• cropping

• sharpening

• noise reduction

• cloning of minor distractions

Not allowed

• adding elements

• replacing skies

• generative fill

• AI-generated imagery

• compositing external images

The difficulty is that generative removal looks similar to traditional cloning.

8. Practical guidance for camera clubs

A workable rule set emerging in many places is:

Safe edits (generally acceptable)

• exposure and colour adjustment

• cropping

• sharpening

• noise reduction

• lens corrections

• dodging and burning

• cloning/healing using existing pixels

Grey area

• AI upscaling

• AI denoise

• AI masking

These analyse the image but don’t invent new scene content.

Usually prohibited in “photography” categories

• Generative remove

• Generative fill

• Generative expand

• sky replacement using external images

• prompt-based generation

Because new scene content is created.

9. A useful rule of thumb

A simple conceptual test:

“Could the missing pixels theoretically be reconstructed from the original photo?”

If yes → editing
If no → generation

Examples:

Remove dust spot via clone: Reconstruction.

Heal small branch: Reconstruction.

Remove person via generative fill: Generation.

Expand canvas with new mountains; Generation.

Your observation about the Lightroom tool is correct:
When “Use Generative AI” is enabled, Lightroom is not borrowing pixels from the image — it is synthesising them.


Quotations for the new Year

Every year, you make a resolution to change yourself.
This year, make a resolution to be yourself.  ~ Annon.

Art is what we call…the thing an artist does. It’s not the medium or the oil or the price or whether it hangs on a wall or you eat it. What matters, what makes it art, is that the person who made it overcame the resistance, ignored the voice of doubt and made something worth making. Something risky. Something human. Art is not in the …eye of the beholder. It’s in the soul of the artist.  ~ Seth Godin.

Sharpness is a bourgeois concept.  ~ Henri Cartier-Breson.

Isn’t it remarkable how photography has advanced without improving?  ~Charles Sheeler, remarking to Ansel Adams.

Great photography is about depth of feeling, not depth of field.  ~ Peter Adams.

You don’t make a photograph just with a camera. You bring to the act of photography all the pictures you have seen, the books you have read, the music you have heard, the people you have loved.  ~ Unknown.

 If you can smell the street by looking at the photo, it’s a street photograph. ~ Bruce Gilden.

Photography is an immediate reaction; drawing is a meditation.  ~ Henri Cartier-Bresson.

A photographer is like a cod, which produces a million eggs in order that one may reach maturity.  ~ George Bernard Shaw.

Be yourself. I much prefer seeing something, even it is clumsy, that doesn’t look like somebody else’s work.  ~ William Klein.

If Photoshop is the answer, you’re asking the wrong question.  ~ Dean Farrell.

DJI Air 3S has landed

The idea of buying a Sony A7 V got replaced by a drone. Ever since the DJI Phantom was released in 2013, I've had a case of gear acquisition syndrome, but with a mighty effort, I resisted it. Recently, I read that the DJI Mavic 4 Pro had landed in the marketplace with a Hasselblad 100 MP APS-C sensor, two other cameras with different focal lengths and lots of other impressive specs. I was hooked. Then reality set in again. It was the most sophisticated camera drone yet, but its weight meant that I would have to register it, and I thought it might be too difficult for a raw beginner to fly. I did some research and settled on the next best, the DJI Air 3s.

https://store.dji.com/au/product/dji-air-3s-fly-more-combo-rc-2?from=site-nav&vid=173571

The Air 3s also has impressive specs, including two cameras, the main one having a 1” sensor, but not a Hasselblad lens. It has facial recognition, subject tracking, and automated flight settings, such as orbiting a selected subject. Cool! The control software, with sophisticated obstacle avoidance utilising Lidar and a host of other sensors, is impressive. The return-to-home feature doesn’t use GPS technology. It memorises the outward-bound flight path, then retraces it.

Without dipping into the voluminous settings, I flew it from a crowded launch area without crashing! To better understand its capabilities, I need to work through the settings and learn to work the joysticks instinctively so that I can concentrate on framing images. One of my beliefs is that good photography depends on good composition*, which in turn depends on camera position and orientation. This device will open a whole world of possibilities regardless of whether the aircraft height is three metres or 100 metres. The future looks interesting.

  • Good composition and a score of other things!

Note: The Department of Civil Aviation has rules! However, they have a number of recommended apps that make it easy. I use ‘OpenSky’.

The School of Architecture in the ‘60s

With advancing age, one is prone to reminiscing about the past, often through rose coloured glasses. In such a mood, I came across this forgotten epistle hidden deep within my hard drive. It was penned by Senior Building Science Lecturer Derrick Kendrick and delivered on the occasion of the 50th anniversary of the graduation of his most skilled and admiring students. It’s worth noting that the first year architecture class comprised 45 students, none of whom were female—such deprivation! Five years later, at graduation, only 18 remained. This was due in part to Professor Rolf (ex-British Army) Jensen’s belief, referred to by Derrick, that it was not impossible to teach everything. The attrition might also have been caused by students fleeing to an arts course where there were many women.

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